{"id":"W6977191990","doi":"10.6084/m9.figshare.26985595.v1","title":"Additional file 2 of Track and dive-based movement metrics do not predict the number of prey encountered by a marine predator","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Track (disk drive); Movement (music); Predation; Predator","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001769062,0.001187823,0.00155831,0.001743089,0.0007575657,0.001761586,0.00213947,0.001680991,0.8113315],"category_scores_gemma":[0.03762075,0.000745502,0.001444176,0.002613513,0.0003233649,0.001781162,0.0009312672,0.001206136,0.135845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008776376,"about_ca_system_score_gemma":0.001612833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01270539,"about_ca_topic_score_gemma":0.02032455,"domain_scores_codex":[0.999267,0.0001492343,0.0001156251,0.0002220578,0.0001495599,0.00009632482],"domain_scores_gemma":[0.970028,0.02547291,0.001014264,0.001345127,0.001808763,0.0003309585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0006167079,0.0001422458,0.006977092,0.003230394,0.0001356358,0.0001233439,0.00008511563,0.001544775,0.0001187855,0.001136722,0.9761946,0.009694636],"study_design_scores_gemma":[0.009031643,0.0005174767,0.04887966,0.004466,0.0007084665,0.0007925904,0.0006801928,0.01013072,0.001347144,0.02211872,0.9010555,0.0002719024],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.000280074,0.00001443656,0.0003255906,0.00005900413,0.00001802274,0.00004183788,0.9983682,0.0004002029,0.0004926337],"genre_scores_gemma":[0.01652998,0.0001060366,0.004866559,0.0004964508,0.00008746729,0.001945221,0.964552,0.001847695,0.009568518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8113315,"threshold_uncertainty_score":0.2691128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01735978515623509,"score_gpt":0.2415777397323349,"score_spread":0.2242179545760998,"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."}}