{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001071946,0.00009976344,0.0001648551,0.0005062029,0.00007310738,0.00008721864,0.0005918485,0.00007305652,0.00006692741],"category_scores_gemma":[0.0008597639,0.00009068758,0.0001188842,0.001439787,0.00001589832,0.0002763873,0.0001179525,0.00006943347,0.00004475344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000751453,"about_ca_system_score_gemma":0.00004106314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002688993,"about_ca_topic_score_gemma":0.0000303663,"domain_scores_codex":[0.9986331,0.00000566165,0.0002434147,0.0003493946,0.0003881835,0.0003802028],"domain_scores_gemma":[0.9975418,0.001639956,0.00003428021,0.0004990149,0.0001469344,0.000137982],"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":[0.00003005919,0.0001023846,0.2329518,0.00002811465,0.0002983466,0.00002051509,0.0001496388,0.02298691,0.0002174779,0.003778951,0.0377533,0.7016825],"study_design_scores_gemma":[0.0006146268,0.0002721373,0.2737109,0.00000597587,0.00006734379,0.00001233156,0.000006082868,0.7088149,0.005684737,0.002485125,0.007952111,0.0003737278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02124327,0.00001962879,0.9779171,0.00006655379,0.0001470837,0.0001627231,0.000003938566,0.0003755061,0.00006420356],"genre_scores_gemma":[0.3833716,0.000001088756,0.6160882,0.00006807287,0.00001456252,0.00001197138,0.00003656411,0.000006907155,0.0004010986],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7013088,"threshold_uncertainty_score":0.3698132,"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."}}