{"id":"W6967671804","doi":"10.5281/zenodo.12193924","title":"HOTSSea v1 Forcings - HRDPS","year":2016,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Fisheries and Oceans Canada","funders":"","keywords":"Climate system; Climate change; Climate model; Sea surface temperature; High resolution","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009845687,0.002475729,0.001518748,0.001699208,0.0007743901,0.001567173,0.003197499,0.001785126,0.0402971],"category_scores_gemma":[0.00355564,0.0008496111,0.001995734,0.003572824,0.0004688987,0.001256038,0.001607605,0.002189527,0.07694529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001605368,"about_ca_system_score_gemma":0.002100111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04937503,"about_ca_topic_score_gemma":0.0803951,"domain_scores_codex":[0.9992115,0.0001609622,0.00006271801,0.0002432083,0.000203996,0.0001174282],"domain_scores_gemma":[0.9990228,0.0001400339,0.00005858116,0.0003560515,0.0003357557,0.00008672188],"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":[0.0000530488,0.00002714426,0.0009895356,0.0002252944,0.00004543969,0.00002295891,0.00002152468,0.003253163,0.0001499772,0.0005610556,0.9923221,0.002328733],"study_design_scores_gemma":[0.0004415566,0.00003157612,0.005717719,0.0002043626,0.00004911717,0.00008401833,0.0001211403,0.009785404,0.001344173,0.003594129,0.9785499,0.0000769762],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006395774,0.00006435068,0.0002807175,0.00009071059,0.0000673717,0.00001646791,0.9960312,0.001906287,0.0009033188],"genre_scores_gemma":[0.0009634994,0.00003130062,0.0005772118,0.0000247622,0.00001046099,0.00005801599,0.9972852,0.0002693363,0.0007801922],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04937503,"threshold_uncertainty_score":0.1348072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03577906947008622,"score_gpt":0.2592926533993099,"score_spread":0.2235135839292237,"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."}}