{"id":"W4398663925","doi":"10.7910/dvn/n4risx/fuomyr","title":"F75_follow_up.tab","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Computer science; Mathematics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001069453,0.001489686,0.00135146,0.002607971,0.000644616,0.002077307,0.00194043,0.001796472,0.3215036],"category_scores_gemma":[0.006988558,0.0007009198,0.001125108,0.003750427,0.0002965276,0.001206969,0.001162195,0.001110471,0.2098445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001454312,"about_ca_system_score_gemma":0.001649918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02403859,"about_ca_topic_score_gemma":0.03389342,"domain_scores_codex":[0.9993436,0.0000756097,0.00009301651,0.00022374,0.0001000362,0.0001639127],"domain_scores_gemma":[0.996849,0.001118895,0.0004033355,0.0006140016,0.0007114499,0.000303328],"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":[0.0001104307,0.00002215501,0.001054058,0.0003338813,0.00002154784,0.00001297667,0.000008829092,0.00009705137,0.00004185424,0.0001788225,0.9960658,0.002052598],"study_design_scores_gemma":[0.0009755669,0.0000745449,0.01231224,0.0004523881,0.00007062045,0.00010976,0.00007081097,0.0003632095,0.0004498408,0.001358086,0.9837077,0.00005524512],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008129288,0.00002169474,0.00002109463,0.00003775955,0.00001569082,0.000008022011,0.9992724,0.0001189063,0.0004231338],"genre_scores_gemma":[0.0006779947,0.00004093778,0.0001262617,0.0001130832,0.00002118211,0.000082762,0.9969248,0.00009842957,0.001914502],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6784964,"threshold_uncertainty_score":0.9677927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04533995616353281,"score_gpt":0.2170737970663607,"score_spread":0.1717338409028279,"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."}}