{"id":"W4399452538","doi":"10.3354/meps14630","title":"Forecasted changes to the timing of Pacific herring Clupea pallasii spawn in a warming ocean","year":2024,"lang":"en","type":"article","venue":"Marine Ecology Progress Series","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Spawn (biology); Pacific herring; Clupea; Herring; Environmental science; Oceanography; Global warming; Effects of global warming on oceans; Fishery; Climate change; Geology; Biology; Fish <Actinopterygii>","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":[],"consensus_categories":[],"category_scores_codex":[0.0002948329,0.0004179699,0.0001663021,0.0002817503,0.0003163196,0.0006673702,0.0004310022,0.0004888004,0.0006803063],"category_scores_gemma":[0.0008092375,0.0003103027,0.0004536678,0.0003051301,0.0002661115,0.0003722677,0.0002597351,0.0004421719,0.00009567284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001860261,"about_ca_system_score_gemma":0.001414339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.355435,"about_ca_topic_score_gemma":0.291625,"domain_scores_codex":[0.99992,0.00001167337,0.000004933107,0.00003492232,0.00001053714,0.0000179906],"domain_scores_gemma":[0.9997831,0.00005582511,0.00004647215,0.00001301235,0.00005372095,0.00004788235],"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":[0.00007787139,0.00004358693,0.1759606,0.000013223,0.00007303582,0.00007974841,0.00004135983,0.8198665,0.0009594047,0.0002879089,0.0004044366,0.002192306],"study_design_scores_gemma":[0.00002653267,0.00004764394,0.07923854,0.0000071288,0.00004831596,0.0000207304,0.00008647615,0.9195513,0.0002739665,0.0001989413,0.0004832617,0.0000171737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979925,0.00004121134,0.0007102176,0.00008384621,0.00001023392,0.000003581751,0.0005751071,0.00003869793,0.0005445027],"genre_scores_gemma":[0.9988074,0.00003737688,0.0004081487,0.00001170411,0.00000256573,0.000003804429,0.0005021214,0.000003690419,0.0002231444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.355435,"threshold_uncertainty_score":0.7067324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01932791202914363,"score_gpt":0.2594517153309853,"score_spread":0.2401238033018416,"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."}}