{"id":"W4353094231","doi":"10.1016/j.cie.2023.109170","title":"Solving resource-constrained project scheduling problems under different activity assumptions","year":2023,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Resource-Constrained Project Scheduling","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Job shop scheduling; Computer science; Preemption; Scheduling (production processes); Heuristic; Mathematical optimization; Operations research; Interpretability; Artificial intelligence; Mathematics; Schedule","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":[0.005375077,0.001097507,0.001921827,0.000949266,0.0005905007,0.001888449,0.001772755,0.002073168,0.002527639],"category_scores_gemma":[0.01717384,0.0009740564,0.001383524,0.001567356,0.0009030561,0.002280853,0.0009352157,0.001772886,0.0001428566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00162876,"about_ca_system_score_gemma":0.00301841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0106946,"about_ca_topic_score_gemma":0.005583216,"domain_scores_codex":[0.9975359,0.001294495,0.0001207326,0.0003476902,0.0002411166,0.0004599469],"domain_scores_gemma":[0.9805107,0.01766261,0.0005991266,0.0003458477,0.0005090757,0.0003726963],"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":[0.000179888,0.00007777308,0.0003578903,0.00009286442,0.00003404739,0.0000454307,0.00002912133,0.9898935,0.0003434742,0.004003097,0.0001781514,0.004764827],"study_design_scores_gemma":[0.00004514354,0.00004300038,0.0001742753,0.000008105292,0.00001511266,0.000007686484,0.00002620976,0.9961229,0.0002832182,0.003197304,0.00007148589,0.000005551185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5713099,0.0006473338,0.4177594,0.0008187043,0.00009458589,0.0003245918,0.0006444256,0.0001914255,0.008209541],"genre_scores_gemma":[0.9120753,0.0003529091,0.0853452,0.00007460408,0.00005205488,0.000242459,0.0004507645,0.00005097226,0.001355667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0106946,"threshold_uncertainty_score":0.02842647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1983876127189261,"score_gpt":0.3453401446975087,"score_spread":0.1469525319785826,"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."}}