{"id":"W3043078559","doi":"10.3390/computers9030057","title":"ERF: An Empirical Recommender Framework for Ascertaining Appropriate Learning Materials from Stack Overflow Discussions","year":2020,"lang":"en","type":"article","venue":"Computers","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University","funders":"","keywords":"Computer science; Python (programming language); Recommender system; Documentation; World Wide Web; Empirical research; Matching (statistics); Information retrieval; Artificial intelligence; Machine learning; Programming language","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":[0.01442946,0.001475167,0.001523038,0.00883244,0.001196087,0.002243958,0.003020543,0.002499522,0.00534017],"category_scores_gemma":[0.04431899,0.0007519976,0.001231537,0.004455893,0.0007173687,0.003773708,0.001604607,0.001876883,0.001942347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001433735,"about_ca_system_score_gemma":0.001832892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01910211,"about_ca_topic_score_gemma":0.03197663,"domain_scores_codex":[0.9934294,0.00368429,0.0005409968,0.001236096,0.0008976267,0.0002116649],"domain_scores_gemma":[0.9643583,0.02719605,0.001853695,0.002329993,0.003670011,0.0005919306],"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":[0.001627039,0.002058496,0.1839961,0.001913411,0.001028619,0.0005290085,0.0045533,0.07360519,0.009241971,0.03156964,0.02804047,0.6618367],"study_design_scores_gemma":[0.0001320606,0.0004393916,0.02820564,0.0001655894,0.0001832787,0.0002386483,0.0008068179,0.9400325,0.002861799,0.01585792,0.01093422,0.0001419704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0984103,0.001321591,0.88592,0.0008580756,0.00007689852,0.001112968,0.005436827,0.003331793,0.003531573],"genre_scores_gemma":[0.4987239,0.0005492767,0.4845932,0.0002225443,0.0001640085,0.001123697,0.01037939,0.0001803498,0.004063673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01910211,"threshold_uncertainty_score":0.07631123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0953893547179278,"score_gpt":0.3337515061552247,"score_spread":0.2383621514372969,"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."}}