{"id":"W2148316074","doi":"10.1002/spip.164","title":"IMMoS: a methodology for integrated measurement, modelling and simulation","year":2002,"lang":"en","type":"article","venue":"Software Process Improvement and Practice","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Novelty; Process (computing); Component (thermodynamics); Systems engineering; Software; Industrial engineering; System dynamics; Empirical research; Software engineering; Engineering; Artificial intelligence","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":[0.002149735,0.0001953973,0.000188926,0.0001001588,0.0002045193,0.0002726932,0.000234076,0.0001032574,0.000006935445],"category_scores_gemma":[0.005054947,0.0001794539,0.00002851337,0.0002245915,0.0000284412,0.002050067,0.00009481508,0.0001869188,0.000001286461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003246035,"about_ca_system_score_gemma":0.00002597962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003388433,"about_ca_topic_score_gemma":0.000001710561,"domain_scores_codex":[0.9986426,0.0001173634,0.0002632905,0.0004611989,0.0002546035,0.000260975],"domain_scores_gemma":[0.9956996,0.003247715,0.0002423234,0.0002351427,0.0004897254,0.00008546431],"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":[0.000191449,0.0001610682,0.00009310005,0.0005096975,0.0001504742,0.000006665798,0.003365353,0.0155099,0.0004667332,0.002650399,0.000297645,0.9765975],"study_design_scores_gemma":[0.0006112205,0.000567744,0.00000575492,0.00005228669,0.0000908,0.00004394774,0.0001637888,0.9342864,0.001128058,0.01338241,0.04930728,0.0003603717],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006956634,0.002565113,0.9942551,0.001224254,0.0001489465,0.0005060667,0.000004179329,0.0005319611,0.00006875556],"genre_scores_gemma":[0.233874,0.0004413757,0.7649161,0.0005263091,0.00004600222,0.0001368824,0.000002512391,0.00001777542,0.00003903164],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9762372,"threshold_uncertainty_score":0.7317917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1605950262362506,"score_gpt":0.3499547941458936,"score_spread":0.189359767909643,"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."}}