{"id":"W2020316880","doi":"10.1145/1039174.1039188","title":"Report on MSR 2004","year":2005,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Software Engineering Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Presentation (obstetrics); Session (web analytics); Computer science; Software; Reuse; Process (computing); Software engineering; Software development; World Wide Web; Data science; 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","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005546866,0.0004336971,0.0003390817,0.00044356,0.0001230149,0.000225843,0.00235654,0.0001866947,0.00005457227],"category_scores_gemma":[0.3063732,0.0004490563,0.0001590417,0.0008533261,0.00003170187,0.0006386003,0.0006462961,0.000608147,0.0006672748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002605554,"about_ca_system_score_gemma":0.0001159733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001892113,"about_ca_topic_score_gemma":0.000001626807,"domain_scores_codex":[0.9969058,0.00002276206,0.0004533438,0.0008623867,0.0008535602,0.0009021628],"domain_scores_gemma":[0.9256798,0.07050347,0.00009402938,0.003151343,0.0001796234,0.0003917155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000242842,0.0004192608,0.6720294,0.000340746,0.000198155,0.002054387,0.0007212661,0.1648806,0.002158233,0.004071261,0.01826508,0.1348373],"study_design_scores_gemma":[0.00149923,0.0005009756,0.7185132,0.0005072808,0.00002898771,0.001470193,0.00000399123,0.008183241,0.04702269,0.0001369325,0.2192381,0.002895146],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2811235,0.001537562,0.7020738,0.003062957,0.001901258,0.0005268793,0.00001363517,0.009736705,0.00002369732],"genre_scores_gemma":[0.7603165,0.00001407584,0.2385533,0.0002070145,0.0004772049,0.00006150611,0.00001210511,0.00007827216,0.0002800631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.479193,"threshold_uncertainty_score":0.9997961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01739211010709344,"score_gpt":0.2603353913010394,"score_spread":0.242943281193946,"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."}}