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2014 dtag toolbox  (MathWorks Inc)


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    MathWorks Inc 2014 dtag toolbox
    2014 Dtag Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/2014 dtag toolbox/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    2014 dtag toolbox - by Bioz Stars, 2026-04
    90/100 stars

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    Map of study areas of Dtag deployments on resident killer whales in Washington State, United States and British Columbia, Canada (a). NRKW population (b) and SRKW population (c) were tagged on opposite ends of Vancouver Island (female = purple, male = green, unknown sex = blue).

    Journal: Behavioral Ecology

    Article Title: Divergent foraging strategies between populations of sympatric matrilineal killer whales

    doi: 10.1093/beheco/arad002

    Figure Lengend Snippet: Map of study areas of Dtag deployments on resident killer whales in Washington State, United States and British Columbia, Canada (a). NRKW population (b) and SRKW population (c) were tagged on opposite ends of Vancouver Island (female = purple, male = green, unknown sex = blue).

    Article Snippet: Because the Dtags did not contain GPS sensors, we used the 2014 Dtag toolbox in MATLAB to dead-reckon the accelerometer and magnetometer data to create best estimates of tracks, by identifying the next position in time based on the previous position ( ).

    Techniques:

    Summary of analyzed Dtag deployments in Northern and Southern resident killer whale populations between 2009 and 2014, ordered by population, sex, and age

    Journal: Behavioral Ecology

    Article Title: Divergent foraging strategies between populations of sympatric matrilineal killer whales

    doi: 10.1093/beheco/arad002

    Figure Lengend Snippet: Summary of analyzed Dtag deployments in Northern and Southern resident killer whale populations between 2009 and 2014, ordered by population, sex, and age

    Article Snippet: Because the Dtags did not contain GPS sensors, we used the 2014 Dtag toolbox in MATLAB to dead-reckon the accelerometer and magnetometer data to create best estimates of tracks, by identifying the next position in time based on the previous position ( ).

    Techniques: Northern Blot