{"id":"W6892189841","doi":"10.5064/f6gzgcjb/hsemad","title":"Lum_53028.Patient_SC_2017.07.18_Alberta.pdf","year":2022,"lang":"nl","type":"dataset","venue":"Syracuse University Qualitative Data Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute of Nursing Research; National Institutes of Health","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003520482,0.001281256,0.001207754,0.003689055,0.0014037,0.003484785,0.002924865,0.002062719,0.3978479],"category_scores_gemma":[0.02485501,0.001233941,0.001247614,0.007401612,0.0006146819,0.001448393,0.002751208,0.001587827,0.2221956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005015174,"about_ca_system_score_gemma":0.008929824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1018084,"about_ca_topic_score_gemma":0.1655905,"domain_scores_codex":[0.9981337,0.0004748342,0.0003332599,0.0003608912,0.0003735343,0.0003237739],"domain_scores_gemma":[0.9877139,0.005632876,0.0008411298,0.001864168,0.003041805,0.0009059826],"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":[0.00005086866,0.000009590104,0.0003478008,0.00057044,0.000009168832,0.000008390972,0.00003893464,0.00006076829,0.00002036333,0.0004223175,0.9959003,0.002560931],"study_design_scores_gemma":[0.0005660331,0.00002285934,0.003907582,0.001675297,0.00003545,0.00004644862,0.0002771645,0.0002376817,0.0002355053,0.00194471,0.9910034,0.0000478882],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005600911,0.00003649482,0.00006812678,0.0001185402,0.00002024673,0.00003251342,0.9977794,0.0001466698,0.001741925],"genre_scores_gemma":[0.0009193044,0.0001713737,0.0006797435,0.000216876,0.00002100139,0.0009669957,0.9913375,0.0001836566,0.005503458],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6021521,"threshold_uncertainty_score":0.858897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06824076107031134,"score_gpt":0.3319588683834373,"score_spread":0.2637181073131259,"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."}}