{"id":"W3081943439","doi":"10.1007/s10664-020-09863-2","title":"CROKAGE: effective solution recommendation for programming tasks by leveraging crowd knowledge","year":2020,"lang":"en","type":"article","venue":"Empirical Software Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Leverage (statistics); Code (set theory); Information retrieval; Task (project management); Relevance (law); Programming language; 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":[0.001768933,0.002050791,0.001661678,0.005668929,0.001287634,0.001562816,0.002317245,0.002852032,0.00532426],"category_scores_gemma":[0.009762625,0.0007053831,0.001127334,0.002604997,0.0006490595,0.003445993,0.002566908,0.001834855,0.002623967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008308554,"about_ca_system_score_gemma":0.00201768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01655002,"about_ca_topic_score_gemma":0.03988067,"domain_scores_codex":[0.9983054,0.0003967806,0.00006344386,0.0005462648,0.0005312573,0.0001567643],"domain_scores_gemma":[0.9972267,0.0013028,0.0001474812,0.0006167785,0.0004809543,0.0002252318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001622596,0.002131168,0.01057224,0.0007313925,0.000523725,0.0002771157,0.0003885941,0.06307398,0.01443699,0.005037503,0.09135307,0.8098516],"study_design_scores_gemma":[0.0002480451,0.0002829508,0.001863273,0.00006461775,0.0001133227,0.0001170286,0.0001448789,0.9708827,0.005056873,0.009590792,0.0115682,0.00006726633],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1616168,0.006738643,0.7502533,0.001993004,0.001242016,0.001461876,0.004862349,0.05210987,0.01972216],"genre_scores_gemma":[0.4182077,0.0008349739,0.5584208,0.0007808633,0.0002825813,0.0006767238,0.007718083,0.001003255,0.01207505],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01655002,"threshold_uncertainty_score":0.03290737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03546418867217926,"score_gpt":0.3080167954479544,"score_spread":0.2725526067757751,"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."}}