{"id":"W2097710325","doi":"10.1145/1082983.1083180","title":"A design for evidence - based soft research","year":2005,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Software Engineering Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Software engineering; Process (computing); Architecture; Data science; Empirical evidence; Triangulation; Management science; Systems engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.272111,0.001807652,0.005071568,0.01978501,0.006555756,0.01868712,0.007244592,0.01263222,0.05357883],"category_scores_gemma":[0.3529066,0.003431556,0.006171012,0.01691321,0.009348892,0.01658926,0.01778911,0.01046345,0.01143409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01304251,"about_ca_system_score_gemma":0.03438767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001133418,"about_ca_topic_score_gemma":0.001585893,"domain_scores_codex":[0.5863895,0.3318872,0.04123367,0.01686407,0.01980701,0.003818595],"domain_scores_gemma":[0.5443506,0.3110794,0.01752754,0.06402895,0.0518479,0.01116568],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.004333536,0.00103945,0.002450412,0.04109932,0.001030872,0.0009683683,0.01220723,0.002362479,0.002208441,0.5513555,0.03661883,0.3443255],"study_design_scores_gemma":[0.00713949,0.003331162,0.001991999,0.03209453,0.001649641,0.0006276495,0.009093968,0.003404295,0.002885615,0.2661338,0.6713269,0.000320926],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006323515,0.005373621,0.5565718,0.02863818,0.006633097,0.3311059,0.004998325,0.001341784,0.05901391],"genre_scores_gemma":[0.01631385,0.001196348,0.6850675,0.004126823,0.0002291095,0.2890674,0.0005270271,0.0001468907,0.003325104],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7278889,"threshold_uncertainty_score":0.8976167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1335202288425324,"score_gpt":0.3485745111298977,"score_spread":0.2150542822873653,"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."}}