{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.05663077,0.001178596,0.0009030488,0.002677698,0.01075359,0.008210137,0.00410343,0.006226843,0.01047323],"category_scores_gemma":[0.1303073,0.0008568909,0.0008979025,0.004838248,0.01206354,0.01518515,0.0162406,0.004786226,0.004354159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00266581,"about_ca_system_score_gemma":0.003217308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002754307,"about_ca_topic_score_gemma":0.003547865,"domain_scores_codex":[0.9195863,0.05741516,0.00354312,0.005514211,0.01202233,0.001918767],"domain_scores_gemma":[0.7823628,0.17406,0.003299068,0.02423957,0.01335184,0.002686775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002166935,0.00730808,0.009635972,0.004221566,0.000128107,0.002456319,0.3556941,0.004952781,0.02079295,0.1396049,0.01833462,0.4347037],"study_design_scores_gemma":[0.001671775,0.003869091,0.01005991,0.003202037,0.0002748939,0.002765442,0.1588971,0.02394159,0.08216464,0.2660478,0.446427,0.0006787824],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5021276,0.002671791,0.2958623,0.005594366,0.001002815,0.006542647,0.001197669,0.004025123,0.1809756],"genre_scores_gemma":[0.6647494,0.001426448,0.3004606,0.0009467615,0.0001622665,0.005695524,0.001242618,0.001666268,0.0236501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9958966,"threshold_uncertainty_score":0.2994958,"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."}}