{"id":"W1994504150","doi":"10.5539/cis.v2n3p64","title":"Positive Affects Inducer on Software Quality","year":2009,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Software Engineering Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Utara Malaysia","keywords":"Agile software development; Computer science; Extreme programming; Metric (unit); Quality (philosophy); Software; Contentment; Empirical research; Affect (linguistics); Extreme programming practices; Software development; Software engineering; Psychology; Statistics; Software development process; Operations management; Social psychology; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001680639,0.0003614081,0.0001893237,0.0005716714,0.000771638,0.001456124,0.0001639509,0.0003298331,0.002751832],"category_scores_gemma":[0.01297095,0.0001406639,0.0002697871,0.0002955471,0.000901903,0.0004867421,0.001559701,0.0006371323,0.0002202623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005692209,"about_ca_system_score_gemma":0.000298913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003644514,"about_ca_topic_score_gemma":0.0004304192,"domain_scores_codex":[0.9969308,0.00147817,0.0001122259,0.0001722433,0.001073998,0.0002326104],"domain_scores_gemma":[0.9812647,0.01076646,0.003211927,0.0007889526,0.002130565,0.001837443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00143651,0.001237726,0.5756605,0.00113255,0.0003545841,0.001905348,0.03580655,0.003232888,0.05122251,0.02073386,0.002357151,0.3049197],"study_design_scores_gemma":[0.00003420201,0.001480984,0.9589192,0.0001269751,0.0002295629,0.0006951986,0.009171609,0.002324317,0.009716049,0.005828943,0.01138973,0.0000832923],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9608211,0.0003179719,0.003502802,0.0002757976,0.00003948055,0.00004105594,0.0000371097,0.00005002159,0.03491458],"genre_scores_gemma":[0.998655,0.00007882339,0.0004922985,0.00003890526,0.00001391313,0.0000129494,0.000008212669,0.000006129683,0.0006938318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002751832,"threshold_uncertainty_score":0.009205759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0192490592782205,"score_gpt":0.3006171555897824,"score_spread":0.2813680963115618,"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."}}