{"id":"W2150439624","doi":"10.1002/smr.519","title":"Studying software evolution of large object‐oriented software systems using an ETGM algorithm","year":2010,"lang":"en","type":"article","venue":"Journal of Software Evolution and Process","topic":"Software Engineering Research","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Algorithm; Software; Scalability; Oracle; Software evolution; Software system; Theoretical computer science; Data mining; Software construction; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002149428,0.000353486,0.0006179607,0.0008676645,0.0004147211,0.0002195814,0.001044798,0.000305664,0.00001136674],"category_scores_gemma":[0.003617326,0.0003287211,0.0001496235,0.001371531,0.0001355177,0.00237214,0.0002662184,0.001072348,0.000003154077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003441974,"about_ca_system_score_gemma":0.0009299676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009795956,"about_ca_topic_score_gemma":0.00001497232,"domain_scores_codex":[0.9961944,0.0001801642,0.001011714,0.0005082132,0.001437274,0.0006682205],"domain_scores_gemma":[0.9949945,0.0005965836,0.0008532022,0.0005780508,0.002523004,0.0004546444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002373238,0.002220146,0.8958313,0.002997249,0.0005194359,0.0002441867,0.008084469,0.02246849,0.004509801,0.002719421,0.0004984195,0.0596697],"study_design_scores_gemma":[0.01207514,0.004381685,0.4898891,0.004248441,0.0004626841,0.008045572,0.005681129,0.457645,0.003358046,0.007678846,0.002765383,0.003768991],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3266913,0.001741946,0.6693578,0.00001565144,0.001731079,0.0002172382,0.00002395655,0.0002200329,0.000001039987],"genre_scores_gemma":[0.7955739,0.00002077874,0.2038761,0.00001275993,0.000438138,0.000009364119,0.000004250626,0.00004150777,0.00002320633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4688826,"threshold_uncertainty_score":0.9999165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01770398146278333,"score_gpt":0.2931408894074464,"score_spread":0.275436907944663,"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."}}