{"id":"W152522724","doi":"10.5281/zenodo.1417422","title":"Data Dictionary: Metadata For Phonograph Records.","year":2006,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Metadata; Computer science; Data dictionary; Digitization; Information retrieval; Interoperability; Data mapping; Semantic interoperability; Phonograph; Data element; Digital library; Annotation; Meta Data Services; Process (computing); Data retrieval; World Wide Web; Database; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001910459,0.001021896,0.001264239,0.008416168,0.001411592,0.004059457,0.003334108,0.002226892,0.06320824],"category_scores_gemma":[0.01360365,0.00100492,0.0007460688,0.01116389,0.0007139709,0.008145755,0.004757107,0.002544255,0.07755811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009054491,"about_ca_system_score_gemma":0.003921072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008617926,"about_ca_topic_score_gemma":0.009704246,"domain_scores_codex":[0.998173,0.000253006,0.0005189019,0.0002604159,0.0006476601,0.0001469543],"domain_scores_gemma":[0.9884504,0.002081818,0.0007578216,0.00434179,0.003434154,0.0009341112],"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":[0.0005001575,0.0001241313,0.002328305,0.001242714,0.00004551515,0.0002804839,0.000372741,0.0007622895,0.005709816,0.01545524,0.8442578,0.1289208],"study_design_scores_gemma":[0.00009929699,0.00004751644,0.002022803,0.0003066799,0.00003800916,0.0003522265,0.0002701276,0.001978279,0.00569187,0.008091982,0.9810096,0.00009162955],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002481165,0.0005930662,0.1523805,0.001567805,0.001050771,0.0005714901,0.7692159,0.04734634,0.02479302],"genre_scores_gemma":[0.01439657,0.0008910131,0.08073656,0.00066399,0.0003002333,0.0006018832,0.8749674,0.007363748,0.02007857],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06320824,"threshold_uncertainty_score":0.2114527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06002829412537313,"score_gpt":0.2804445112757214,"score_spread":0.2204162171503483,"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."}}