{"id":"W3097646272","doi":"10.1002/ece3.7035","title":"Parameter redundancy in Jolly‐Seber tag loss models","year":2021,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Redundancy (engineering); Population; Statistics; Model parameter; Computer science; Mark and recapture; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.008675055,0.001437416,0.001903333,0.001529818,0.0005851962,0.001571513,0.003182597,0.00211711,0.001597957],"category_scores_gemma":[0.03019037,0.001182187,0.001510787,0.001124768,0.002397457,0.00368593,0.002250567,0.001907752,0.0003930587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001295283,"about_ca_system_score_gemma":0.0006267363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002218267,"about_ca_topic_score_gemma":0.001383404,"domain_scores_codex":[0.9965745,0.00179253,0.0001915576,0.0006425843,0.0005015156,0.0002974671],"domain_scores_gemma":[0.974375,0.01890291,0.003437014,0.002314789,0.0007244945,0.0002457855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001658137,0.00006380751,0.006807559,0.00008393941,0.0001151859,0.0003559023,0.0003773756,0.9363762,0.001522705,0.04326861,0.0004357135,0.01042706],"study_design_scores_gemma":[0.00001042011,0.0000416385,0.0008744204,0.00001244337,0.00003248598,0.0001039622,0.0000258743,0.9689159,0.0003691045,0.02928433,0.0003079983,0.00002154472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2129895,0.0004908191,0.7821744,0.0004254082,0.00002967309,0.00009165463,0.0003060463,0.000398463,0.003093975],"genre_scores_gemma":[0.9468814,0.0002405184,0.04888344,0.0001200299,0.00003496054,0.0002096147,0.0003075596,0.0001261855,0.003196178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008675055,"threshold_uncertainty_score":0.04587859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01036884435107819,"score_gpt":0.2084688860721075,"score_spread":0.1981000417210293,"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."}}