{"id":"W6950676045","doi":"10.5683/sp/f4bxob","title":"Group 8 Data","year":2017,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Group (periodic table); Presentation (obstetrics); Climate change; Carbon dioxide; Greenhouse gas; Greenhouse effect","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":[0.001702592,0.001730164,0.001261322,0.004266607,0.001128813,0.002759496,0.002768969,0.001820475,0.08111033],"category_scores_gemma":[0.007575983,0.0006367423,0.001141362,0.007300566,0.0005391856,0.001489009,0.002453379,0.002059639,0.1241379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001928593,"about_ca_system_score_gemma":0.004518559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03178945,"about_ca_topic_score_gemma":0.04956998,"domain_scores_codex":[0.9977179,0.0003782428,0.0002782996,0.0005269137,0.0006844388,0.0004141977],"domain_scores_gemma":[0.9960414,0.0006450862,0.0003672319,0.00102311,0.001495234,0.0004278551],"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":[0.00005584439,0.00001888664,0.0007051251,0.0002159834,0.00001415114,0.00001444163,0.0000236268,0.0001398394,0.0001022721,0.0005816434,0.9967444,0.001383733],"study_design_scores_gemma":[0.0001013904,0.00001138591,0.002043748,0.0001305019,0.00001413291,0.00002578594,0.0001001585,0.0001227244,0.0002443691,0.0007172425,0.9964712,0.00001734175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001466766,0.00002932277,0.00004428171,0.00005956648,0.00003803629,0.00001540707,0.9984477,0.0002143697,0.001004681],"genre_scores_gemma":[0.0002606529,0.00002585649,0.0001500163,0.00003990104,0.000007327346,0.00006449938,0.9986346,0.00006150742,0.0007555906],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08111033,"threshold_uncertainty_score":0.2713411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08706423273894287,"score_gpt":0.3577749343445084,"score_spread":0.2707107016055655,"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."}}