{"id":"W4412703839","doi":"10.1145/3696630.3728564","title":"Behind the Hot Fix: Demystifying Hot Fixing Industrial Practices at Zühlke and Beyond","year":2025,"lang":"en","type":"article","venue":"","topic":"Sustainable Industrial Ecology","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nickel Institute","funders":"","keywords":"Computer science","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":[0.0006185719,0.0002012626,0.0002380718,0.0001488224,0.0003338648,0.0001497667,0.0002428378,0.0003708744,0.0004238433],"category_scores_gemma":[0.001558191,0.0001598424,0.0000407158,0.0002810086,0.00008891567,0.0002720187,0.0002492445,0.0006172028,0.00002114638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003256334,"about_ca_system_score_gemma":0.0001331846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002033716,"about_ca_topic_score_gemma":0.0005225152,"domain_scores_codex":[0.998753,0.0000966512,0.000310428,0.0002605122,0.0001327728,0.00044662],"domain_scores_gemma":[0.997982,0.00152111,0.0001106035,0.0002714095,0.00004483435,0.00007001846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001580328,0.0002047109,0.06765784,0.0006792501,0.002557376,0.0004683886,0.006481713,0.08909455,0.008697484,0.01680505,0.6011033,0.20467],"study_design_scores_gemma":[0.006379123,0.0002150155,0.01032345,0.0001319573,0.0005543497,0.0001345587,0.01317686,0.0527545,0.01362408,0.001836695,0.8996436,0.001225804],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9213133,0.0007570756,0.0002108792,0.004280604,0.001822716,0.0006122253,0.000005179362,0.000320627,0.07067735],"genre_scores_gemma":[0.9925197,0.00005089865,0.0001698838,0.0004123645,0.0004295613,0.00005135596,0.000004758504,0.00002735874,0.006334062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2985403,"threshold_uncertainty_score":0.6518185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.038894286483942,"score_gpt":0.2741696948355583,"score_spread":0.2352754083516163,"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."}}