{"id":"W2773168634","doi":"10.32920/ryerson.14638275.v1","title":"ORCID: Using API Calls to Assess Metadata Completeness","year":2021,"lang":"en","type":"article","venue":"","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Metadata; Interoperability; Completeness (order theory); Computer science; World Wide Web; Publishing; Library science; Information retrieval; Political science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003132984,0.00008545709,0.0001531839,0.00008494322,0.0001338123,0.001505943,0.00119476,0.00002561605,0.000117774],"category_scores_gemma":[0.00002818015,0.00006799905,0.00003859064,0.001046545,0.00001409135,0.01110698,0.0006916277,0.00004299489,0.0003041877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001892581,"about_ca_system_score_gemma":0.0002304245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005893214,"about_ca_topic_score_gemma":0.000005463677,"domain_scores_codex":[0.9987673,0.00005950168,0.0002820776,0.0002669489,0.0003916512,0.000232534],"domain_scores_gemma":[0.9988937,0.00004508616,0.00005323758,0.0007098886,0.0001402635,0.0001577576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003534087,0.0001128183,0.006009643,0.00008020294,0.00006517653,0.0001316833,0.004626835,0.005719092,0.1126304,0.8016604,0.0441733,0.02478692],"study_design_scores_gemma":[0.0003625491,0.00004871988,0.004330301,0.00005203883,0.00000353148,0.0002780739,0.001512868,0.3877338,0.2005021,0.0009113203,0.4035812,0.0006835092],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02436977,0.00001775565,0.9598365,0.00127179,0.0006114332,0.00008509756,0.000004190516,0.0001062168,0.01369719],"genre_scores_gemma":[0.6289279,0.000002743041,0.3481773,0.0161817,0.0001212506,0.000007309602,0.0000166083,0.000007161832,0.006558023],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8007491,"threshold_uncertainty_score":0.9995306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2281464184956896,"score_gpt":0.3222594818071802,"score_spread":0.09411306331149055,"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."}}