{"id":"W2128683249","doi":"10.1109/promise.2007.5","title":"Decision Support Analysis for Software Effort Estimation by Analogy","year":2007,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Analogy; Selection (genetic algorithm); Weighting; Context (archaeology); Process (computing); Adaptation (eye); Decision support system; Similarity (geometry); Decision analysis; Machine learning; Software; Artificial intelligence; Personalization; Data mining; Mathematics","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":[0.01284512,0.001684029,0.001850145,0.004863123,0.001077174,0.003043253,0.001488431,0.001642044,0.007772656],"category_scores_gemma":[0.06858286,0.0004939947,0.001485492,0.003725037,0.001288872,0.003630474,0.001971072,0.001887258,0.0006676863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002182723,"about_ca_system_score_gemma":0.002038646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001882199,"about_ca_topic_score_gemma":0.001065156,"domain_scores_codex":[0.9828302,0.01153459,0.000734518,0.0008823766,0.003646925,0.0003714121],"domain_scores_gemma":[0.9385224,0.05442516,0.002071529,0.001384256,0.00324958,0.000346978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006326673,0.0005481515,0.004674166,0.0008189197,0.0002671174,0.0004076182,0.0007757967,0.3961678,0.002068306,0.3132478,0.002333031,0.2780587],"study_design_scores_gemma":[0.0000727904,0.0001889138,0.0005853362,0.00006960323,0.00005342093,0.00006990178,0.0001427418,0.8934166,0.0009764545,0.102647,0.001740341,0.00003699142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03448503,0.0002918756,0.9590568,0.0004430249,0.00003210581,0.0003251385,0.0001214812,0.0002440967,0.005000413],"genre_scores_gemma":[0.4607821,0.0003335938,0.5365775,0.0001022831,0.00006168705,0.000817507,0.0002508825,0.00005073609,0.001023742],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01284512,"threshold_uncertainty_score":0.06793225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01435796703714535,"score_gpt":0.3080868266492115,"score_spread":0.2937288596120661,"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."}}