{"id":"W4393822527","doi":"10.5281/zenodo.8245898","title":"Proxy SIT Canadian Arctic - dataset","year":2023,"lang":"en","type":"dataset","venue":"Bristol Research (University of Bristol)","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Manitoba","funders":"","keywords":"Proxy (statistics); Arctic; The arctic; Geography; Physical geography; Environmental science; Climatology; Computer science; Oceanography; Geology; Machine learning","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":[0.0008130904,0.002203495,0.001267866,0.004830657,0.002183321,0.002549288,0.003142386,0.001322773,0.04644231],"category_scores_gemma":[0.004951774,0.000680046,0.001056171,0.01328806,0.0004899921,0.001154564,0.001588894,0.001911746,0.04172135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01058476,"about_ca_system_score_gemma":0.02198104,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8710495,"about_ca_topic_score_gemma":0.9271917,"domain_scores_codex":[0.9987165,0.00008822857,0.00009446264,0.0003548623,0.0004804782,0.0002655657],"domain_scores_gemma":[0.9964192,0.0003047771,0.0001649815,0.000409341,0.002374233,0.0003274468],"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":[0.00003492467,0.000008543588,0.001272046,0.0002404607,0.00003598653,0.0000194464,0.00002001207,0.0004715114,0.00007698393,0.0005471105,0.9955987,0.001674274],"study_design_scores_gemma":[0.00008136343,0.000005865166,0.008412459,0.00020777,0.00003605199,0.00004027763,0.000102279,0.0008259126,0.0003610235,0.0006843447,0.9891931,0.00004955074],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008843395,0.00003483152,0.00002925164,0.0000255689,0.00000903326,0.000004638134,0.9991813,0.0001320577,0.0004947826],"genre_scores_gemma":[0.0002772779,0.00003213563,0.0001616681,0.00001444918,0.000001926757,0.00001645323,0.9991054,0.00004504638,0.0003456848],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1289505,"threshold_uncertainty_score":0.2594199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04332354523056044,"score_gpt":0.2822545973425926,"score_spread":0.2389310521120322,"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."}}