{"id":"W2915897795","doi":"10.5334/kula.49","title":"Towards Open Annotation: Examples and Experiments","year":2019,"lang":"en","type":"article","venue":"KULA knowledge creation dissemination and preservation studies","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Annotation; Usability; World Wide Web; Reading (process); Computer science; Multimedia; Political science; Human–computer interaction; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003168322,0.0001633015,0.0002210887,0.0001164222,0.0004727722,0.001250993,0.0001394446,0.00003573256,0.0009233538],"category_scores_gemma":[0.0001738995,0.0001430954,0.00002472297,0.00005924252,0.0001739901,0.002083667,0.0002391862,0.00005896417,0.00004381784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003251641,"about_ca_system_score_gemma":0.0000175189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003955419,"about_ca_topic_score_gemma":0.0002218759,"domain_scores_codex":[0.9990826,0.0000622038,0.0002814071,0.0002818599,0.0001621447,0.0001298099],"domain_scores_gemma":[0.998911,0.0002273666,0.0001184414,0.0001399832,0.0005514196,0.00005179238],"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":[0.00003766171,0.00007968279,0.00505005,0.0001389272,0.00008012047,2.442892e-7,0.2352176,5.644979e-7,0.00009744771,0.7229678,0.007925783,0.02840412],"study_design_scores_gemma":[0.0007656277,0.0001260044,0.03449461,0.0002689607,0.00003674952,0.000001539298,0.0764375,0.0002923527,0.0004041547,0.01428504,0.8725365,0.0003508939],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4463168,0.00391989,0.00001121472,0.0005208962,0.0002551469,0.0004632682,0.00001816439,0.00005215086,0.5484424],"genre_scores_gemma":[0.7579405,0.0003503291,0.00006576769,0.00009132435,0.0001145353,0.0001032042,0.0001160613,0.00001242926,0.2412058],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8646108,"threshold_uncertainty_score":0.9999899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1673996113905645,"score_gpt":0.3918177755495113,"score_spread":0.2244181641589468,"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."}}