{"id":"W2808500230","doi":"10.29173/iq618","title":"IASSIST Session 5P Summary: Big Picture Metadata, June 5, Toronto, CA","year":2015,"lang":"en","type":"article","venue":"IASSIST Quarterly","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Metadata; Computer science; World Wide Web; Library science; Information retrieval","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":[],"category_scores_codex":[0.01053871,0.001805704,0.00198601,0.006247331,0.007447463,0.01666404,0.002814026,0.005568507,0.6365125],"category_scores_gemma":[0.01695553,0.001387227,0.001913332,0.007431095,0.001401397,0.007057791,0.007975999,0.004155362,0.5622776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007966245,"about_ca_system_score_gemma":0.02245432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1295463,"about_ca_topic_score_gemma":0.2982273,"domain_scores_codex":[0.9939505,0.0004931293,0.0002814612,0.000520054,0.003846765,0.0009082375],"domain_scores_gemma":[0.9706538,0.001908937,0.0009839276,0.003287441,0.01511522,0.008050683],"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":[0.00001034869,0.000004730859,0.00001885349,0.00001497835,8.413805e-7,0.000003362539,0.000007430446,0.000008354211,0.00002854494,0.0001341615,0.9983433,0.001425159],"study_design_scores_gemma":[0.00001761308,0.00001005547,0.0004892182,0.0000526032,0.000003467526,0.000005460566,0.00005286391,0.00005757261,0.00009211912,0.0002747634,0.9989325,0.00001173008],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0009907912,0.002262666,0.005675651,0.04007656,0.03455661,0.003020344,0.1449886,0.01994547,0.7484833],"genre_scores_gemma":[0.003065641,0.001315154,0.002685918,0.006416732,0.007102969,0.001200314,0.08878166,0.006261167,0.8831704],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6365125,"threshold_uncertainty_score":0.5184708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05062850382956199,"score_gpt":0.2277789367640318,"score_spread":0.1771504329344698,"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."}}