{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007670253,0.0003089877,0.0006750036,0.0001330063,0.0002514431,0.000435209,0.0004720037,0.0001509287,0.00323167],"category_scores_gemma":[0.00005720991,0.0003105131,0.0002192452,0.0001646627,0.0001307125,0.00108616,0.00008865009,0.000146169,0.01053723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004225473,"about_ca_system_score_gemma":0.00005839968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002304717,"about_ca_topic_score_gemma":0.002473015,"domain_scores_codex":[0.9978176,0.00002894093,0.0007262338,0.0008049136,0.00009324137,0.0005290636],"domain_scores_gemma":[0.9984635,0.00003850148,0.000391856,0.0007248374,0.00006678599,0.0003145825],"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":[0.00004785013,0.0001799719,0.007750723,0.0000252315,0.0002118597,0.00001650449,0.003056397,0.00000669806,0.00001243754,0.02616375,0.955046,0.007482594],"study_design_scores_gemma":[0.001068976,0.0001462793,0.0072594,0.00002053497,0.0000295732,0.000005404969,0.005110642,0.000106994,0.00001479615,0.002149349,0.9836081,0.0004799909],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.05589487,0.01505426,0.002362495,0.002070968,0.03340466,0.0005584563,0.003326126,0.0002946003,0.8870336],"genre_scores_gemma":[0.4226626,0.0001041322,0.0005923862,0.000483691,0.0006837655,0.00004590328,0.0001742725,0.00004573233,0.5752075],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3667677,"threshold_uncertainty_score":0.9999347,"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."}}