{"id":"W4393381429","doi":"10.22541/essoar.171199516.69691755/v1","title":"Assessing the time of emergence of global ocean fish biomass using ensemble climate to fish simulations","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Mesopelagic zone; Pelagic zone; Trophic level; Biomass (ecology); Environmental science; Climate change; Global warming; Fishery; Oceanography; Fish <Actinopterygii>; Ecology; Climatology; Geology; Biology","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":[0.0007436221,0.0006664117,0.000582219,0.0004768853,0.0004508323,0.0007045742,0.0006713101,0.001100625,0.001307214],"category_scores_gemma":[0.002377928,0.0003208866,0.001061698,0.0005756645,0.0003860524,0.0007513472,0.0007058693,0.0008883334,0.0001468831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006251312,"about_ca_system_score_gemma":0.001107865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05886424,"about_ca_topic_score_gemma":0.03193146,"domain_scores_codex":[0.9998672,0.00004778556,0.000008124548,0.00003410992,0.0000151681,0.00002768218],"domain_scores_gemma":[0.9993268,0.0003509563,0.00007576333,0.00005853827,0.00009495096,0.00009302231],"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":[0.00008561943,0.0000503673,0.02181515,0.00003585764,0.0001325459,0.00006318096,0.00003178711,0.9735497,0.0006246001,0.0006830252,0.0006154014,0.002312674],"study_design_scores_gemma":[0.00002662725,0.00002916028,0.006397079,0.000007829627,0.00002764007,0.000007355549,0.00003446334,0.9926168,0.0001251267,0.0003711531,0.0003440704,0.000012637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883564,0.0002408767,0.006345736,0.0003475673,0.00006439673,0.00002246189,0.001778609,0.0001614321,0.002682486],"genre_scores_gemma":[0.9952793,0.0001264958,0.002405597,0.00006847319,0.00002254847,0.00004080666,0.001689172,0.00003544096,0.0003321627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05886424,"threshold_uncertainty_score":0.1170432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0441291137595324,"score_gpt":0.3523723046262155,"score_spread":0.3082431908666832,"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."}}