{"id":"W2103920581","doi":"10.1109/achi.2008.33","title":"Examining Programmer's Cognitive Skills Using Regular Language","year":2008,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University; Dalhousie University","funders":"","keywords":"Computer science; Regular expression; Programmer; Notation; Pattern matching; Cognition; Task (project management); Programming language; Alternation (linguistics); Matching (statistics); Natural language; Completeness (order theory); Artificial intelligence; Natural language processing; Mathematics; Arithmetic; Linguistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002046203,0.0003364623,0.000171593,0.001211751,0.0001902456,0.001492476,0.00043116,0.0004888475,0.002973867],"category_scores_gemma":[0.03991193,0.0002099151,0.0002146105,0.0004695025,0.0005058759,0.001468729,0.0006491158,0.0007144221,0.000680856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001949456,"about_ca_system_score_gemma":0.0004289543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001259219,"about_ca_topic_score_gemma":0.001864471,"domain_scores_codex":[0.9987143,0.0003655267,0.0001513299,0.0002438941,0.0003993984,0.0001255404],"domain_scores_gemma":[0.9459903,0.03601732,0.008356474,0.003113466,0.005195605,0.001326905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004905182,0.001337063,0.7463362,0.0004540859,0.0001582302,0.000381191,0.02656269,0.004223275,0.02306083,0.002341012,0.00239374,0.1922612],"study_design_scores_gemma":[0.00007519095,0.001814852,0.9566978,0.0001159331,0.00009437824,0.001087428,0.008897758,0.01238368,0.008370896,0.004610467,0.005757255,0.00009440327],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929175,0.00004334666,0.001602336,0.00007103624,0.000004050868,0.00002050398,0.00004831599,0.00006700108,0.005225959],"genre_scores_gemma":[0.9958565,0.00007472316,0.002129671,0.00004536968,0.000005070022,0.00002357679,0.0000941906,0.00001707512,0.00175373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002973867,"threshold_uncertainty_score":0.01082146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04375681411313004,"score_gpt":0.2936822245585169,"score_spread":0.2499254104453869,"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."}}