{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001800839,0.0003167183,0.0005375682,0.0007622131,0.0008927059,0.00005689209,0.002435188,0.0005351519,0.008013505],"category_scores_gemma":[0.0002951908,0.0003857321,0.0001509224,0.001700981,0.001456054,0.0002472446,0.001562126,0.001651964,0.0424414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002007995,"about_ca_system_score_gemma":0.0006240079,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9261525,"about_ca_topic_score_gemma":0.7424969,"domain_scores_codex":[0.995519,0.0005215203,0.0002705439,0.0009540127,0.001570671,0.001164228],"domain_scores_gemma":[0.9970106,0.0002184648,0.0002267069,0.001427869,0.0001021189,0.001014162],"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":[0.00004174423,0.00009092384,0.0001098003,0.0001978162,0.0000794874,0.001075208,0.00008862904,0.00007243892,0.00001588582,0.000005014379,0.9974795,0.0007435389],"study_design_scores_gemma":[0.0003250368,0.0001489315,0.0007914911,0.0001141843,0.00007092355,0.00001897635,0.0004660569,0.0001580924,0.00000155869,0.0002263216,0.9972917,0.0003867032],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007639611,0.0001555282,0.00000327619,0.0008970057,0.0002065439,0.0006947192,0.995099,0.00002956416,0.002150414],"genre_scores_gemma":[0.0005535661,0.000911295,0.0001094683,0.00005272962,0.00005263205,0.000002133474,0.9876233,0.00003766149,0.01065719],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1836556,"threshold_uncertainty_score":0.9998595,"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."}}