{"id":"W6888850405","doi":"10.24431/rw1k46f","title":"Development and testing of mechanistic fitness-based models to predict habitat choice, behavior, and recruitment of juvenile Chinook salmon in the Arctic-Yukon-Kuskokwim region","year":2020,"lang":"en","type":"dataset","venue":"Axiom Data Science","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chinook wind; Juvenile; Dominance (genetics); Captivity; Predation; Minnow","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003634608,0.0005108286,0.000751541,0.0007383655,0.0002999021,0.0001671638,0.00387597,0.0001312133,0.000003285551],"category_scores_gemma":[0.002526387,0.0004062801,0.00002453458,0.00267508,0.001016357,0.0009194049,0.002484243,0.0004198789,0.00001947466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002363223,"about_ca_system_score_gemma":0.001463637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001971371,"about_ca_topic_score_gemma":0.001818603,"domain_scores_codex":[0.9945926,0.0002127664,0.001070164,0.001701173,0.00181144,0.0006118464],"domain_scores_gemma":[0.9952883,0.0007980216,0.0008696613,0.00251987,0.000230108,0.0002940491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009276032,0.004415076,0.01260267,0.007952127,0.000161676,0.0008168344,0.008232485,0.002633948,0.0366041,0.00129678,0.8980306,0.02632614],"study_design_scores_gemma":[0.01253094,0.007276741,0.1776001,0.02753543,0.003848188,0.000975265,0.00455575,0.2084659,0.01918333,0.002106135,0.5266134,0.009308865],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03798954,0.0001297342,0.0004768428,0.00008447644,0.0001158361,0.003157096,0.9579979,0.00003375062,0.00001483479],"genre_scores_gemma":[0.201672,0.00004134352,0.02397108,0.0002183418,0.00004021539,0.000600123,0.7733861,0.00006854205,0.000002244685],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3714172,"threshold_uncertainty_score":0.9998389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2310830364375154,"score_gpt":0.3495906355032355,"score_spread":0.1185075990657201,"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."}}