{"id":"W2162624365","doi":"10.1109/ase.2009.65","title":"Automatically Recommending Triage Decisions for Pragmatic Reuse Tasks","year":2009,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; McGill University","funders":"","keywords":"Computer science; Reuse; Task (project management); Software engineering; Plan (archaeology); Process (computing); Triage; Software; Recommender system; Human–computer interaction; Code (set theory); Code reuse; Software system; World Wide Web; Programming language; Systems engineering","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0009657036,0.0001082069,0.0001621731,0.0001919817,0.0001107881,0.0002362657,0.001587696,0.00005399985,0.00004141308],"category_scores_gemma":[0.0154927,0.00009001071,0.00007334225,0.0004555836,0.000009316578,0.000336984,0.0002166148,0.0001228305,0.00008232942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006798708,"about_ca_system_score_gemma":0.00005797698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001361104,"about_ca_topic_score_gemma":5.408351e-7,"domain_scores_codex":[0.9987225,0.00003920609,0.0002765526,0.0002796061,0.000297817,0.0003843184],"domain_scores_gemma":[0.992708,0.005888865,0.00003228036,0.001138649,0.00007500962,0.0001572057],"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":[0.00001835705,0.0003143361,0.0001987513,0.00003993488,0.00004073418,0.00003344092,0.0009398516,0.00054396,0.001784813,0.245741,0.1823996,0.5679452],"study_design_scores_gemma":[0.001814067,0.0006811106,0.01113586,0.0001676969,0.000009801686,0.00004208856,0.00002135529,0.8531762,0.00158579,0.114022,0.0168375,0.0005065055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004743278,0.00001795328,0.9849725,0.00778368,0.0001908308,0.0004205517,0.00000140982,0.0008824404,0.0009873788],"genre_scores_gemma":[0.16642,0.000003977045,0.8325175,0.0004001073,0.00003958239,0.00004360092,0.000002031711,0.000008716908,0.0005644747],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8526323,"threshold_uncertainty_score":0.9928002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03942043419170047,"score_gpt":0.3359819658516376,"score_spread":0.2965615316599371,"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."}}