{"id":"W4394057682","doi":"10.5281/zenodo.1484460","title":"kennek12/HUG-5_validation: HUG-5 Validation- pre print","year":2018,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Psychology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.00437648,0.003419596,0.001962664,0.003674795,0.001392397,0.004068285,0.004650779,0.003933131,0.1630538],"category_scores_gemma":[0.02201346,0.001143037,0.002767069,0.003795487,0.001003773,0.001953934,0.003248644,0.002807716,0.1924612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001371369,"about_ca_system_score_gemma":0.003173048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01344296,"about_ca_topic_score_gemma":0.02809643,"domain_scores_codex":[0.9967354,0.0008291011,0.0003343273,0.0009531394,0.0007296149,0.0004184698],"domain_scores_gemma":[0.9918278,0.002792418,0.0004624471,0.002768923,0.001683465,0.0004650303],"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":[0.00005878065,0.00002199541,0.0006386841,0.0003658309,0.00003731917,0.00001650053,0.00001386315,0.0001938847,0.00006089889,0.0002600469,0.9968041,0.001528069],"study_design_scores_gemma":[0.000873524,0.00005583211,0.005966263,0.0006449444,0.0001090685,0.0001697087,0.00009680719,0.001591565,0.0009754316,0.003798414,0.9856313,0.00008699708],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002605605,0.00009696829,0.0003553921,0.000153658,0.0001086916,0.00003567685,0.995967,0.001944318,0.001077679],"genre_scores_gemma":[0.0006329451,0.00004175447,0.0007524507,0.0001136314,0.00002081643,0.0001721084,0.996622,0.0004956172,0.001148779],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1630538,"threshold_uncertainty_score":0.5454694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.293635978004036,"score_gpt":0.3958368101357968,"score_spread":0.1022008321317608,"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."}}