{"id":"W6977861036","doi":"10.7910/dvn/pkjufn/2kcif1","title":"FCC2003.104.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Process (computing); Identification (biology); Product (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":[],"category_scores_codex":[0.00132644,0.002356715,0.001653991,0.00358845,0.0007183378,0.003409355,0.003260287,0.002505749,0.1655968],"category_scores_gemma":[0.009102985,0.0008934375,0.001305097,0.007775256,0.0004778575,0.001379763,0.001774283,0.001536285,0.1913391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001745062,"about_ca_system_score_gemma":0.002216405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03327423,"about_ca_topic_score_gemma":0.0448323,"domain_scores_codex":[0.9989598,0.0002319138,0.0001124413,0.0003251349,0.0002010305,0.0001697277],"domain_scores_gemma":[0.9972515,0.0008435974,0.0002660126,0.000711237,0.0006147958,0.0003128615],"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":[0.00005152682,0.000008642415,0.0003592375,0.0003084574,0.00002312367,0.000009898566,0.000008168097,0.0001902108,0.00003149982,0.0003124689,0.9976285,0.001068101],"study_design_scores_gemma":[0.0004280233,0.00002303107,0.002438152,0.0003718064,0.00003687665,0.00005284533,0.00003810799,0.0006558028,0.00024675,0.001889484,0.9937906,0.00002860806],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004032149,0.00004530904,0.00003351713,0.00005427827,0.00001601135,0.000003426996,0.9987941,0.0003784048,0.0006345534],"genre_scores_gemma":[0.0003192445,0.00005263785,0.0001381566,0.00008562989,0.0000100918,0.0000282427,0.9986073,0.0001508374,0.0006077208],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8344033,"threshold_uncertainty_score":0.5539763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02341228980309299,"score_gpt":0.2622581986356582,"score_spread":0.2388459088325653,"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."}}