{"id":"W4398424987","doi":"10.7910/dvn/gwicxo/okkf72","title":"PROSPERED data manual - bbreaks 032018.docx","year":2018,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Natural language processing; Computer graphics (images); Programming language; Information retrieval; Database","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":[0.003840639,0.003397479,0.002237339,0.007910165,0.001863584,0.004855871,0.004439473,0.002982493,0.2995788],"category_scores_gemma":[0.01906629,0.00124755,0.0020007,0.009294724,0.001197158,0.003420371,0.003977688,0.003329617,0.3733759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002372974,"about_ca_system_score_gemma":0.00536889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02255633,"about_ca_topic_score_gemma":0.05538505,"domain_scores_codex":[0.9970298,0.0006197287,0.0004138157,0.0007565622,0.0007127817,0.0004672772],"domain_scores_gemma":[0.9904346,0.002792088,0.000486287,0.002746979,0.002728348,0.0008116486],"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":[0.00001836897,0.000008604299,0.0001284175,0.0002022759,0.000008088767,0.000005539128,0.000009891396,0.00004354099,0.0000306573,0.0001779201,0.9985929,0.0007737462],"study_design_scores_gemma":[0.0002190341,0.00001695237,0.001320222,0.0002877834,0.0000212517,0.00005227991,0.00007490744,0.0002397884,0.0003366528,0.001629369,0.9957706,0.00003108449],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008367649,0.00006237928,0.0001208642,0.0001131905,0.00005871061,0.00002149144,0.9970958,0.001147909,0.001295998],"genre_scores_gemma":[0.000225654,0.00004240338,0.0003904818,0.00006920244,0.00001472573,0.0001188424,0.9971922,0.0004444902,0.001502008],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7004212,"threshold_uncertainty_score":0.9990659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03893798991570866,"score_gpt":0.3005754507162237,"score_spread":0.261637460800515,"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."}}