{"id":"W6894258207","doi":"10.5683/sp3/o1brah","title":"Creating Something from Nothing: Working with Synthetic Files","year":2004,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Toronto","funders":"","keywords":"Microdata (statistics); File Transfer Protocol; Presentation (obstetrics); Data presentation; Data file","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":[0.008544577,0.001706538,0.001065588,0.00335864,0.001675619,0.004254718,0.003350973,0.001188204,0.01197943],"category_scores_gemma":[0.04791163,0.001015484,0.001871579,0.006466853,0.001085163,0.006099469,0.004085147,0.002751895,0.01201157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001588092,"about_ca_system_score_gemma":0.001846969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01059688,"about_ca_topic_score_gemma":0.01556894,"domain_scores_codex":[0.9927905,0.002708289,0.0007705208,0.001627802,0.001715569,0.0003872006],"domain_scores_gemma":[0.9717837,0.008238357,0.0006538329,0.01429926,0.003949536,0.001075374],"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":[0.0003897041,0.0002267739,0.004874622,0.0004483495,0.0001488663,0.0002135311,0.0004542202,0.005612638,0.001395458,0.006468639,0.9360762,0.04369102],"study_design_scores_gemma":[0.0003849291,0.0001565616,0.00579789,0.000291576,0.0001254167,0.0005994704,0.001522976,0.03426697,0.0111792,0.028063,0.9174199,0.000191994],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03767455,0.0008557134,0.08445495,0.005270198,0.002871121,0.0009373384,0.7362968,0.1036007,0.02803861],"genre_scores_gemma":[0.03043472,0.0003043576,0.08649667,0.0008866392,0.000126074,0.0007524457,0.8705924,0.006959686,0.003447001],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01197943,"threshold_uncertainty_score":0.04518861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03278352226867432,"score_gpt":0.2634297031070046,"score_spread":0.2306461808383303,"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."}}