{"id":"W6947905639","doi":"10.4230/oasics.evcs.2023.7","title":"Generating Software for Well-Understood Domains","year":2023,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Software; Software development; Software construction; Traceability; Domain (mathematical analysis); Generative grammar; Software framework; Software system; Artifact (error)","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":[],"consensus_categories":[],"category_scores_codex":[0.002491515,0.0007581341,0.0004069537,0.001432361,0.0005900644,0.002038588,0.002032258,0.001125569,0.007200044],"category_scores_gemma":[0.0108314,0.0006730792,0.001991906,0.001008459,0.001077509,0.002970702,0.002814994,0.001524328,0.002888937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007401395,"about_ca_system_score_gemma":0.001180306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007797456,"about_ca_topic_score_gemma":0.00146277,"domain_scores_codex":[0.9988716,0.0002960724,0.0001012791,0.0002530602,0.0004142581,0.00006361013],"domain_scores_gemma":[0.9931715,0.003338764,0.0003391931,0.002110685,0.0008939386,0.000146057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002160173,0.0004306087,0.01737567,0.001503109,0.0002023964,0.001277197,0.004564766,0.09122931,0.05348263,0.1656671,0.02801717,0.6360341],"study_design_scores_gemma":[0.0002361404,0.000254626,0.003054836,0.0003769673,0.0001713711,0.001681589,0.001261928,0.4908247,0.1065409,0.1727603,0.2226764,0.000160298],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03457458,0.0001732588,0.9442705,0.0004483197,0.00008329215,0.0002186501,0.000544308,0.01376516,0.005922026],"genre_scores_gemma":[0.1205315,0.0003192906,0.8657993,0.0001571898,0.00003072991,0.000206747,0.002626395,0.004713957,0.005614872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007200044,"threshold_uncertainty_score":0.02408653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02883043313446245,"score_gpt":0.2635337781162186,"score_spread":0.2347033449817562,"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."}}