{"id":"W6910736551","doi":"10.5064/f6gzgcjb/keztw6","title":"Lum_53079.CarePart_PC_2018.02.04_Alberta.pdf","year":2022,"lang":"de","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":[0.003226552,0.001444104,0.001055909,0.004713642,0.001574485,0.003558545,0.002766606,0.001858416,0.3886243],"category_scores_gemma":[0.01887792,0.001269733,0.001199704,0.00879418,0.0006030811,0.001498391,0.002844435,0.001678999,0.2714257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004369919,"about_ca_system_score_gemma":0.008098934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1055123,"about_ca_topic_score_gemma":0.1881522,"domain_scores_codex":[0.998331,0.0003832662,0.0002417229,0.0003282701,0.0003845798,0.0003312685],"domain_scores_gemma":[0.990473,0.003594338,0.0005889983,0.00174549,0.002857701,0.000740501],"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":[0.00002198284,0.000006408576,0.0002172268,0.0003824715,0.000006102504,0.000004431388,0.00002766115,0.00004575006,0.00002419697,0.0003848108,0.9971601,0.001718922],"study_design_scores_gemma":[0.0002390909,0.00001134994,0.002527418,0.0007856481,0.00001721891,0.00001736088,0.0001793701,0.0001197194,0.0001910179,0.001210225,0.9946728,0.0000286369],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003120589,0.00002312069,0.00004688945,0.00007619282,0.00001732129,0.00002014977,0.9981604,0.0001338676,0.001490853],"genre_scores_gemma":[0.0004314755,0.0001004804,0.0004794654,0.0001256081,0.0000113917,0.0005492262,0.9927422,0.0001714644,0.005388807],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6113757,"threshold_uncertainty_score":0.8720531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0636055451400466,"score_gpt":0.3374697462288018,"score_spread":0.2738642010887552,"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."}}