{"id":"W4297062848","doi":"","title":"A meta-analysis of DDL research 2: Variation, good practice and future work.","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Nursing Diagnosis and Documentation","field":"Nursing","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Variation (astronomy); Work (physics); Computer science; Engineering; Mechanical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01525788,0.000287997,0.0008523133,0.0007831668,0.0003865347,0.0004986956,0.0006819151,0.0003462465,0.0003726949],"category_scores_gemma":[0.002711492,0.000249811,0.0005603413,0.001520507,0.000277976,0.0003185366,0.0005938872,0.0006487444,0.00001413112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001717334,"about_ca_system_score_gemma":0.0001145462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001278272,"about_ca_topic_score_gemma":0.000464977,"domain_scores_codex":[0.9830388,0.01405981,0.0007294173,0.0008714665,0.0009556357,0.000344829],"domain_scores_gemma":[0.9838765,0.00753437,0.0009747024,0.001996017,0.005464511,0.0001538684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0007456517,0.006586201,0.009867106,0.0009175843,0.1602793,0.00001177492,0.1798896,0.0002219914,0.006018094,0.4375708,0.02290489,0.174987],"study_design_scores_gemma":[0.003782748,0.00001249227,0.130161,0.003248999,0.4328591,0.0000197281,0.003848988,0.005173104,0.07683913,0.08070102,0.2603365,0.003017176],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06895027,0.03164443,0.05946926,0.7270765,0.002095185,0.003055147,0.0005970619,0.0004449611,0.1066672],"genre_scores_gemma":[0.9481707,0.001324286,0.04524894,0.0003220216,0.0001289379,0.0002327339,0.0005575107,0.00007612814,0.003938807],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8792204,"threshold_uncertainty_score":0.9999954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0613632414464723,"score_gpt":0.3451651779237427,"score_spread":0.2838019364772704,"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."}}