{"id":"W4234304462","doi":"10.22360/springsim.2017.cns.008","title":"Comparing Quantitative and Comment-Based Ratings for Recommending Open Educational Resources","year":2017,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Open educational resources; Computer science; Recommender system; Quality (philosophy); Similarity (geometry); Educational resources; Sentiment analysis; World Wide Web; Term (time); Information retrieval; Knowledge management; Data science; Artificial intelligence; Psychology","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":[0.0007499721,0.0001038935,0.0001925606,0.00005854777,0.001073312,0.002355027,0.001547204,0.00002871199,0.000009874365],"category_scores_gemma":[0.00009309517,0.00008962523,0.00003136273,0.00002941725,0.00004168041,0.0009182511,0.0007052663,0.0000576095,0.000001857278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002838926,"about_ca_system_score_gemma":0.00003432061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008593433,"about_ca_topic_score_gemma":0.0001687328,"domain_scores_codex":[0.9991978,0.00005000958,0.0002067246,0.0002990052,0.00008235661,0.0001641435],"domain_scores_gemma":[0.9986995,0.0004177065,0.0002552526,0.0004980481,0.00006576863,0.00006368312],"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":[0.00001304773,0.00007121678,0.0418652,0.00004251475,0.00002635631,3.281554e-7,0.0008386113,0.000001588635,0.000155769,0.8862609,0.0604556,0.01026889],"study_design_scores_gemma":[0.003848787,0.0007838329,0.06136069,0.0006351942,0.00001996797,0.00001623932,0.001046924,0.4110549,0.01222807,0.08918352,0.4186738,0.001148078],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00860997,0.00004512696,0.8612182,0.09449323,0.0003149091,0.0008204753,0.000003519314,0.0001052586,0.03438934],"genre_scores_gemma":[0.6055574,0.000001511294,0.3928316,0.001195015,0.00002588845,0.0001282173,0.000002893939,0.000005540319,0.0002519348],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7970774,"threshold_uncertainty_score":0.9986807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1640849323040539,"score_gpt":0.3980992086564042,"score_spread":0.2340142763523503,"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."}}