{"id":"W2793924535","doi":"10.22215/etd/2017-12232","title":"NotesKB: Web-Based Semantic Annotation Tool for Online Multimedia Learning Content","year":2017,"lang":"en","type":"dissertation","venue":"","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Saudi Arabian Cultural Bureau","keywords":"Usability; Computer science; USable; World Wide Web; Multimedia; Semantic Web; Annotation; Web usability; Usability lab; Key (lock); Usability engineering; Human–computer interaction; Artificial intelligence","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":[0.001781482,0.0009791263,0.0004878062,0.003229521,0.0009448495,0.002261853,0.001192369,0.001062012,0.02327057],"category_scores_gemma":[0.008432635,0.0004345048,0.0006102874,0.001786359,0.0007488028,0.005951831,0.002554619,0.001209525,0.01147415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006452128,"about_ca_system_score_gemma":0.001381229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001894313,"about_ca_topic_score_gemma":0.002893454,"domain_scores_codex":[0.9987833,0.0002459098,0.0001444185,0.0001978032,0.0005710504,0.00005758251],"domain_scores_gemma":[0.9954081,0.00241627,0.0003139704,0.000592887,0.0009755412,0.0002932023],"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":[0.0007959469,0.0004343872,0.003087974,0.001813115,0.00004954813,0.0007645686,0.005159856,0.001388503,0.05552513,0.01665513,0.102848,0.8114777],"study_design_scores_gemma":[0.0001882064,0.0004281072,0.009837249,0.00100727,0.0001159998,0.001716668,0.003642411,0.02546566,0.09891402,0.02054673,0.8377958,0.0003418527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04714787,0.0007020193,0.7628409,0.001351363,0.0005589454,0.001338496,0.01492629,0.1404288,0.03070516],"genre_scores_gemma":[0.124537,0.0009306964,0.7748962,0.0004299601,0.0001590023,0.001383742,0.02066401,0.009057025,0.06794242],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02327057,"threshold_uncertainty_score":0.07784784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0809249811761428,"score_gpt":0.38937091310372,"score_spread":0.3084459319275772,"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."}}