{"id":"W2171898463","doi":"10.2744/ccb-0847.1","title":"The Complex Linear Home Range Estimator: Representing the Home Range of River Turtles Moving in Multiple Channels","year":2011,"lang":"en","type":"article","venue":"Chelonian Conservation and Biology","topic":"Turtle Biology and Conservation","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Home range; Estimator; Range (aeronautics); Polygon (computer graphics); Turtle (robot); Biology; Fishery; Habitat; Computer science; Ecology; Statistics; Mathematics; Telecommunications; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008444134,0.0002479609,0.0002764274,0.0008067933,0.0001424458,0.000368764,0.000509239,0.0001945991,0.0009532174],"category_scores_gemma":[0.00227622,0.0001023627,0.0002559486,0.0007813884,0.0002662404,0.0004061874,0.0003738102,0.0001878234,0.0001303944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005406445,"about_ca_system_score_gemma":0.0005859385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08990806,"about_ca_topic_score_gemma":0.1420695,"domain_scores_codex":[0.9997459,0.00009112977,0.00001228023,0.00007010622,0.00005084054,0.00002972524],"domain_scores_gemma":[0.9989723,0.0005150338,0.0002030806,0.0001053542,0.0001665394,0.00003780607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002330088,0.00009544448,0.4440804,0.0001177252,0.0002557856,0.0002506016,0.000432798,0.3291839,0.008767877,0.003175269,0.002439498,0.2109676],"study_design_scores_gemma":[0.00002626746,0.0000818799,0.2002314,0.00001764499,0.00005670898,0.0002158946,0.0001778814,0.7930899,0.002607644,0.001256016,0.002184169,0.00005472666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6432291,0.0003054461,0.3530022,0.00008251289,0.000007962944,0.00006211588,0.001226762,0.0005004891,0.001583312],"genre_scores_gemma":[0.9131092,0.0000777498,0.08533565,0.0000213544,0.000008759816,0.00005153711,0.000709514,0.0000383762,0.0006479863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08990806,"threshold_uncertainty_score":0.1787695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08211968401986912,"score_gpt":0.2608176555012288,"score_spread":0.1786979714813596,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}