{"id":"W3030206985","doi":"10.5703/1288284317041","title":"From Affordable to Open: Evaluating Open Educational Resources","year":2019,"lang":"en","type":"article","venue":"","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Purdue Pharma (Canada)","funders":"","keywords":"Strategist; Presentation (obstetrics); Panel discussion; Library science; Management; Computer science; Open educational resources; Business; Medicine; Advertising; Economics","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.02529766,0.000799355,0.001208917,0.003198072,0.001984761,0.008880965,0.001389547,0.002683372,0.01478757],"category_scores_gemma":[0.164151,0.0004328825,0.002137276,0.002825512,0.002513934,0.01275973,0.006974831,0.002446011,0.002286542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003996436,"about_ca_system_score_gemma":0.002360179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002562628,"about_ca_topic_score_gemma":0.005597936,"domain_scores_codex":[0.9627272,0.01759013,0.004110116,0.001739727,0.01272302,0.001109786],"domain_scores_gemma":[0.8876363,0.08344622,0.008594564,0.004371318,0.01015815,0.005793394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.03841952,0.02703389,0.1295156,0.01421797,0.003293535,0.0006302557,0.02144079,0.01251438,0.00293853,0.03826733,0.04057326,0.671155],"study_design_scores_gemma":[0.01586567,0.1142137,0.3362602,0.01771807,0.007343492,0.0007033127,0.06288401,0.03659257,0.01858306,0.1218211,0.2660851,0.00192973],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8932961,0.005526647,0.00978875,0.001935959,0.0007714875,0.009621397,0.003121978,0.000275217,0.07566234],"genre_scores_gemma":[0.9519599,0.001781589,0.02433805,0.001353501,0.0002047902,0.01045751,0.0030997,0.000175755,0.006629096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9986104,"threshold_uncertainty_score":0.1337884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05391205997290156,"score_gpt":0.381964883313533,"score_spread":0.3280528233406314,"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."}}