{"id":"W4403411684","doi":"10.1016/j.orl.2024.107194","title":"Structured pruning of neural networks for constraints learning","year":2024,"lang":"en","type":"article","venue":"Operations Research Letters","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pruning; Artificial neural network; Computer science; Artificial intelligence; Machine learning; Biology; Botany","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0012122,0.000081293,0.00009864214,0.0002460156,0.0004908443,0.0005942407,0.0004185074,0.0000454996,0.00002376183],"category_scores_gemma":[0.0001826208,0.00007403911,0.00005044532,0.0005595415,0.0001546298,0.0003765338,0.00009953258,0.0005338255,0.000004269478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003627349,"about_ca_system_score_gemma":0.0001172909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003668146,"about_ca_topic_score_gemma":0.00001057354,"domain_scores_codex":[0.9986346,0.0002401903,0.0001833033,0.000288448,0.000285307,0.0003681939],"domain_scores_gemma":[0.9989382,0.000623468,0.00001118109,0.0002108955,0.0001498773,0.00006637195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003556079,0.000004206175,0.0001566694,0.0000413771,0.00002258556,0.00001350151,0.001112883,0.9292481,0.01477382,0.01578,0.003107511,0.0357358],"study_design_scores_gemma":[0.00009535295,0.00006663195,0.00006130319,0.00009667836,0.000002237228,0.000009077974,0.00005722976,0.9974975,0.0007084408,0.00008257693,0.001245255,0.00007774471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0517805,0.0003457376,0.9406917,0.006391283,0.0002448437,0.0002789865,0.000005598934,0.0001127165,0.0001486324],"genre_scores_gemma":[0.9610503,0.00000532019,0.03842155,0.0001678051,0.0001140219,0.00004279389,0.0000246762,0.00001085953,0.0001626927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9092698,"threshold_uncertainty_score":0.5730277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04766301081933947,"score_gpt":0.3484694934558907,"score_spread":0.3008064826365512,"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."}}