{"id":"W4394315508","doi":"10.6084/m9.figshare.9904778","title":"Halifax Buoy Data - 2017","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Buoy; Environmental science; Computer science; Meteorology; Geology; Geography; Oceanography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009718784,0.001801138,0.001059094,0.00466582,0.0006866022,0.002533789,0.001305385,0.001606805,0.05497275],"category_scores_gemma":[0.005666635,0.000645536,0.001090896,0.00784248,0.0004375475,0.001193054,0.001645414,0.001293674,0.06003943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001900542,"about_ca_system_score_gemma":0.003775611,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1426368,"about_ca_topic_score_gemma":0.1810502,"domain_scores_codex":[0.999244,0.0001016361,0.00009064286,0.0001559292,0.0002302928,0.000177633],"domain_scores_gemma":[0.9975373,0.0006050786,0.0003782508,0.0004336293,0.0008010342,0.0002447641],"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":[0.00004146753,0.000006408285,0.001395006,0.0002208056,0.00002355239,0.00001190291,0.00002005271,0.000208229,0.00002835534,0.0003640427,0.9962556,0.001424602],"study_design_scores_gemma":[0.0001470171,0.000007820111,0.01217762,0.0002973798,0.00003339192,0.00002788976,0.0001548254,0.000357725,0.0001776996,0.0008598063,0.9857292,0.00002946847],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001622542,0.00005869228,0.00002118333,0.00009933416,0.00002716238,0.000003162015,0.9989992,0.00007781777,0.0005511809],"genre_scores_gemma":[0.0008770534,0.00009160637,0.0001234066,0.00006577326,0.00001668351,0.00004937091,0.9967981,0.00005864333,0.001919413],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8573632,"threshold_uncertainty_score":0.2836131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2811951583628546,"score_gpt":0.4278607991427499,"score_spread":0.1466656407798953,"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."}}