{"id":"W3040850713","doi":"10.1080/01691864.2020.1786723","title":"A library for constraint consistent learning","year":2020,"lang":"en","type":"article","venue":"Advanced Robotics","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Engineering and Physical Sciences Research Council","keywords":"Reuse; Computer science; Constraint (computer-aided design); Task (project management); Software; Space (punctuation); Implementation; Code (set theory); Null (SQL); Learning curve; Machine learning; Artificial intelligence; State space; Human–computer interaction; Software engineering; Programming language; Data mining; Engineering; Set (abstract data type); Operating system; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002311759,0.002483664,0.001504625,0.003026426,0.00096426,0.003337413,0.005997489,0.002553693,0.1318528],"category_scores_gemma":[0.01376148,0.002121691,0.003215408,0.003769392,0.001046905,0.003753512,0.005157228,0.005055876,0.06799911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001395261,"about_ca_system_score_gemma":0.003335627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004411845,"about_ca_topic_score_gemma":0.008730239,"domain_scores_codex":[0.9972751,0.0004723461,0.0003197702,0.0004432639,0.001308973,0.0001805824],"domain_scores_gemma":[0.995449,0.002260918,0.0002089638,0.001055739,0.0008848459,0.000140424],"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":[0.000224712,0.0001859334,0.0005862161,0.001961,0.0001940036,0.0003558257,0.0001856187,0.04475585,0.003133554,0.1166703,0.2764007,0.5553464],"study_design_scores_gemma":[0.0002210342,0.00005696306,0.0002546843,0.0003582779,0.00004555646,0.0004482736,0.00004105162,0.1943768,0.006894721,0.1687941,0.6284173,0.00009125192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.0002194338,0.0003302137,0.9169652,0.0002444107,0.0001080541,0.0001502411,0.005892978,0.06670494,0.009384507],"genre_scores_gemma":[0.01116546,0.0009803053,0.9157748,0.0007263443,0.0001554814,0.001519367,0.0238711,0.02654978,0.01925732],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1318528,"threshold_uncertainty_score":0.4410914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02585733602643614,"score_gpt":0.2356678145950763,"score_spread":0.2098104785686402,"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."}}