{"id":"W2623939708","doi":"","title":"Toward Common Ground: Metadata Document","year":2017,"lang":"en","type":"article","venue":"The Atrium (University of Guelph)","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metadata; Computer science; Information retrieval; World Wide Web; Database","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005198353,0.00006649978,0.0001339271,0.00005430176,0.0007851847,0.000484504,0.005254203,0.00002791322,0.00003844499],"category_scores_gemma":[0.000009510934,0.00005256761,0.00007923217,0.0001176727,0.0001923989,0.0129759,0.001335716,0.0000682223,0.0001781667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001747887,"about_ca_system_score_gemma":0.00004887932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001257692,"about_ca_topic_score_gemma":0.00002286314,"domain_scores_codex":[0.9992524,0.00004978113,0.0001059118,0.0001361445,0.0003083486,0.0001474381],"domain_scores_gemma":[0.9981831,0.00003454666,0.0002898928,0.001388971,0.00004430053,0.00005916372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00007919429,0.0001038537,0.007536424,0.0001319882,0.000237189,0.00006987805,0.0689872,0.0001451996,0.008383637,0.7765208,0.07036415,0.0674405],"study_design_scores_gemma":[0.001386978,0.0002432577,0.6267275,0.000048855,0.00002984825,0.00005261996,0.01364248,0.01603126,0.0009262633,0.01415314,0.3262492,0.0005085324],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5621723,0.0002027529,0.2938837,0.06233569,0.001775417,0.0005852097,0.00002298269,0.0002344235,0.07878752],"genre_scores_gemma":[0.9950594,0.00002813184,0.001696693,0.0001841004,0.00002705986,7.207287e-8,0.0000023269,0.000001340816,0.003000901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7623676,"threshold_uncertainty_score":0.9763703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03964495418081958,"score_gpt":0.2341611582758844,"score_spread":0.1945162040950648,"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."}}