{"id":"W6948700888","doi":"10.5064/f6gzgcjb/zjs7ht","title":"Lum_53022.CarePart_PC_2017.07.25_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":[0.003465447,0.001441528,0.001100757,0.004693235,0.001706958,0.003686741,0.002907693,0.00190165,0.377934],"category_scores_gemma":[0.01990787,0.001348458,0.001251233,0.009099008,0.0006450363,0.001433574,0.002893666,0.00176692,0.2509765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005133101,"about_ca_system_score_gemma":0.01015508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1518467,"about_ca_topic_score_gemma":0.2646547,"domain_scores_codex":[0.9982744,0.0003966537,0.0002412036,0.0003392305,0.0003991315,0.0003492823],"domain_scores_gemma":[0.9897357,0.003843745,0.0006142724,0.001855725,0.003153725,0.000796849],"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":[0.00002314102,0.000006525234,0.0002337801,0.0004236534,0.000006794035,0.000004591741,0.00003003687,0.00005188554,0.00002385334,0.0004057567,0.9969748,0.001815131],"study_design_scores_gemma":[0.0002583917,0.00001185328,0.002783723,0.000927246,0.00001990176,0.00001770106,0.0002035769,0.0001342944,0.0001941907,0.00131884,0.9940981,0.00003226206],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003362618,0.00002634739,0.00005253574,0.00008061932,0.00001872785,0.00002344905,0.9980959,0.0001352493,0.001533492],"genre_scores_gemma":[0.0004805639,0.0001132153,0.0005520554,0.0001335227,0.000012083,0.0006426196,0.9919818,0.0001771106,0.005907129],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.622066,"threshold_uncertainty_score":0.8873016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06470596028120668,"score_gpt":0.3388264888497768,"score_spread":0.2741205285685702,"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."}}