{"id":"W4398982700","doi":"10.7910/dvn/v1rjpf/8km3mo","title":"iqa20150430_03.txt.gz","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Linguistic, Cultural, and Literary Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Physics","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":[],"category_scores_codex":[0.00161706,0.003331885,0.002232996,0.005704625,0.001363069,0.006535385,0.0049683,0.004093822,0.2743748],"category_scores_gemma":[0.01019286,0.001199899,0.001889156,0.01019523,0.0008982191,0.002886312,0.004595078,0.002555778,0.3313678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002431838,"about_ca_system_score_gemma":0.002804972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0312092,"about_ca_topic_score_gemma":0.04367997,"domain_scores_codex":[0.9986442,0.0002604702,0.0001426233,0.0003805215,0.0002758217,0.0002964344],"domain_scores_gemma":[0.9966979,0.0009615183,0.0003191371,0.000802371,0.0007000219,0.0005190857],"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":[0.00002973164,0.00001050225,0.0002296764,0.0004702689,0.00001735059,0.000008302884,0.00001856742,0.0001057218,0.00003707454,0.0003875978,0.9978577,0.0008275354],"study_design_scores_gemma":[0.0003121147,0.00001694841,0.001565581,0.0003867156,0.00002576811,0.00002458787,0.00009023009,0.0002772426,0.0001792721,0.001726668,0.9953655,0.000029442],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003152198,0.00003791327,0.00002628811,0.00007222922,0.00002374331,0.00000598849,0.9989065,0.0003191112,0.0005767283],"genre_scores_gemma":[0.0002224905,0.00005802411,0.0001294585,0.00007693355,0.00001469376,0.00006710008,0.9984602,0.0001466631,0.0008244085],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7256252,"threshold_uncertainty_score":0.9178753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03268515925790021,"score_gpt":0.2945282667746949,"score_spread":0.2618431075167947,"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."}}