{"id":"W4394538446","doi":"10.6084/m9.figshare.1483401","title":"High Resolution Figures 1 and 2","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resolution (logic); Environmental science; Computer science; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001551869,0.001778995,0.001381819,0.005820628,0.000944867,0.003632806,0.002490536,0.001732875,0.3036599],"category_scores_gemma":[0.01350817,0.0007991159,0.001345565,0.01154829,0.0005374431,0.001915855,0.001778482,0.002256083,0.2908142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002520633,"about_ca_system_score_gemma":0.005023943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06198848,"about_ca_topic_score_gemma":0.1231868,"domain_scores_codex":[0.9981866,0.0002299974,0.0002129578,0.0005109633,0.0005590069,0.0003003722],"domain_scores_gemma":[0.9944569,0.001227612,0.0004340643,0.001185921,0.002323719,0.0003718908],"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":[0.00001452318,0.000005908714,0.0002370055,0.0001684321,0.00001010156,0.000006197862,0.000008047523,0.00009212537,0.00002346529,0.0002833146,0.9984298,0.0007209754],"study_design_scores_gemma":[0.00009770817,0.000005546657,0.003012644,0.0002336759,0.00001638933,0.00002574349,0.00006248994,0.0001148827,0.0001157853,0.001106111,0.9951888,0.00002011994],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003539939,0.00003365229,0.00004097975,0.00004683288,0.00004003591,0.000008411396,0.9988483,0.0001517933,0.0007945987],"genre_scores_gemma":[0.0002940222,0.00005596243,0.0002682259,0.00005387185,0.00001532638,0.00006579149,0.9972084,0.0001458112,0.00189263],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6963401,"threshold_uncertainty_score":0.9932446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09705559362849946,"score_gpt":0.2283544635219805,"score_spread":0.1312988698934811,"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."}}