{"id":"W3026245580","doi":"10.1007/s00442-020-04667-z","title":"Predicting habitat use by the Argentine hake Merluccius hubbsi in a warmer world: inferences from the Middle Holocene","year":2020,"lang":"en","type":"article","venue":"Oecologia","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Arts and Humanities Research Council; Universitat de Barcelona; Universidad Autónoma de Madrid; Agencia Nacional de Promoción Científica y Tecnológica; Consejo Nacional de Investigaciones Científicas y Técnicas; Leverhulme Trust","keywords":"Hake; Holocene; Merluccius; Population; Holocene climatic optimum; Fishing; Biology; Fishery; Ecology; Oceanography; Geology; Paleontology; 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":[0.0001580591,0.0002159439,0.0001478715,0.000548392,0.0003297196,0.000376321,0.0001741487,0.0002733401,0.001223971],"category_scores_gemma":[0.0004649373,0.0001321692,0.0001178082,0.0003354871,0.0002065278,0.0002633925,0.0002684276,0.0001730809,0.0002133903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000428952,"about_ca_system_score_gemma":0.0001354056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09669486,"about_ca_topic_score_gemma":0.2807149,"domain_scores_codex":[0.999965,0.000006550937,0.000001442779,0.00001329115,0.000003455342,0.00001027081],"domain_scores_gemma":[0.9998277,0.00003877993,0.00004887579,0.00001033235,0.00002685072,0.00004748304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001131273,0.00002132166,0.9908371,0.00001012957,0.00003119808,0.00006846499,0.0004575492,0.0006065509,0.00193426,0.00004188987,0.0001625353,0.005715821],"study_design_scores_gemma":[0.000001335371,0.0000076625,0.999099,0.000002629427,0.00000427564,0.00001200417,0.0001918629,0.0004730602,0.0000352917,0.00001117065,0.0001603807,0.000001354611],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994147,0.00004502613,0.00003785301,0.00001216903,9.662015e-7,7.589192e-7,0.00009093803,0.000001635104,0.0003959733],"genre_scores_gemma":[0.9995148,0.00004641556,0.0001004855,0.000006414991,0.000001703872,0.000001386913,0.0001573024,0.000002594792,0.0001688478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09669486,"threshold_uncertainty_score":0.1922641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0359950201169992,"score_gpt":0.2319496575721357,"score_spread":0.1959546374551365,"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."}}