{"id":"W4385342865","doi":"10.4204/eptcs.380.5","title":"Compositional Modeling with Stock and Flow Diagrams","year":2023,"lang":"en","type":"article","venue":"Electronic Proceedings in Theoretical Computer Science","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada; Public Health Agency of Canada; Foundation for the National Institutes of Health","keywords":"Principle of compositionality; Computer science; Story-driven modeling; Programming language; Interaction overview diagram; Semantics (computer science); Theoretical computer science; Stock (firearms); Syntax; Software; Class diagram; Unified Modeling Language; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002601373,0.00100386,0.0006475226,0.001783886,0.001096989,0.002868964,0.001655285,0.001407188,0.007338146],"category_scores_gemma":[0.005895908,0.0007642425,0.002671199,0.001307767,0.002025637,0.004875938,0.002618285,0.001779121,0.001016279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001629423,"about_ca_system_score_gemma":0.002130509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008816258,"about_ca_topic_score_gemma":0.009641089,"domain_scores_codex":[0.9981029,0.0006837401,0.0001563336,0.0003169678,0.0005727461,0.000167216],"domain_scores_gemma":[0.9976698,0.001155229,0.0002108971,0.0004190533,0.0003840383,0.0001610141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002199453,0.00003148105,0.000461583,0.0000543072,0.00002799497,0.0001080009,0.0002624879,0.1066545,0.0009050705,0.8824334,0.000736661,0.008302419],"study_design_scores_gemma":[0.00003225411,0.00002263472,0.0001032276,0.00003658057,0.00004051008,0.00006382484,0.00005546002,0.4150496,0.001175591,0.5588702,0.02452796,0.00002208715],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004650289,0.00008677169,0.9886146,0.0001730958,0.00003169456,0.00005999132,0.0001764658,0.0004067493,0.005800521],"genre_scores_gemma":[0.1973678,0.0006153909,0.7894106,0.0001801878,0.0001019615,0.0005516805,0.0006451635,0.0003649739,0.0107621],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008816258,"threshold_uncertainty_score":0.02454853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0424166694482239,"score_gpt":0.3349286603871206,"score_spread":0.2925119909388967,"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."}}