{"id":"W6930554734","doi":"10.5281/zenodo.11210744","title":"pbs-assess/juvenile-salmon-index: v1.0 as published in Fisheries Research","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Fishing; Fisheries Research; Government (linguistics); Context (archaeology); Work (physics)","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":[0.002650776,0.003279316,0.002290439,0.005943436,0.001103014,0.004703343,0.003997038,0.001759818,0.4133314],"category_scores_gemma":[0.007310169,0.0021893,0.001774781,0.005414124,0.0007098412,0.003589657,0.005386207,0.00204791,0.5442243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009757715,"about_ca_system_score_gemma":0.00267021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0087503,"about_ca_topic_score_gemma":0.00929267,"domain_scores_codex":[0.9985771,0.0001635943,0.0001588421,0.0003864912,0.0004871005,0.0002268925],"domain_scores_gemma":[0.9972167,0.0005520306,0.0002627436,0.0007510079,0.0007374809,0.0004799639],"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":[0.0001753662,0.0000269248,0.001793898,0.000687618,0.00007999869,0.00004253003,0.00007356841,0.0006026111,0.00114652,0.001512483,0.9772916,0.01656693],"study_design_scores_gemma":[0.0001911112,0.00004369281,0.003134008,0.0001926612,0.00006692984,0.0001394669,0.00005367736,0.002502048,0.004184595,0.007245131,0.9821196,0.0001270922],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.0009494451,0.0002235653,0.01483881,0.0001872033,0.0002261158,0.00009066997,0.8559472,0.1121624,0.01537449],"genre_scores_gemma":[0.003932107,0.0001822993,0.01710405,0.0002102568,0.00008649199,0.0003078739,0.8702734,0.09257299,0.01533046],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.4133314,"threshold_uncertainty_score":0.8368116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03315639569403538,"score_gpt":0.2676301978650965,"score_spread":0.2344738021710611,"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."}}