{"id":"W3123543355","doi":"10.1287/msom.2020.0952","title":"Dynamic Type Matching","year":2021,"lang":"en","type":"preprint","venue":"Manufacturing & Service Operations Management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Toronto","funders":"","keywords":"Matching (statistics); Hierarchy; Supply and demand; Disjoint sets; Optimal matching; Type (biology); Mathematical optimization; Computer science; Property (philosophy); Mathematics; Microeconomics; Economics; Statistics; Discrete 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":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004081765,0.001294548,0.00192378,0.001234128,0.001848382,0.005470398,0.005081768,0.005322679,0.04291396],"category_scores_gemma":[0.01342149,0.0009420495,0.00178227,0.003043277,0.002228371,0.006438548,0.003268816,0.002984716,0.004579836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003822231,"about_ca_system_score_gemma":0.004443922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003939928,"about_ca_topic_score_gemma":0.002638252,"domain_scores_codex":[0.9949855,0.002136589,0.0002607027,0.001440095,0.0005408416,0.0006362354],"domain_scores_gemma":[0.9925633,0.004906859,0.0006293547,0.0007251543,0.0005267751,0.0006485721],"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":[0.00037794,0.0004217736,0.001921306,0.0004922991,0.0001124557,0.000648762,0.0003682919,0.1556495,0.0007302374,0.7436875,0.03241334,0.06317651],"study_design_scores_gemma":[0.0001956406,0.0001409801,0.0005125995,0.0001292361,0.00006308477,0.0006731019,0.0004936982,0.3577215,0.0008811154,0.5836532,0.05547839,0.00005751635],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03264913,0.0006188618,0.8726457,0.006637968,0.0004512499,0.001461496,0.003221355,0.0005351374,0.08177914],"genre_scores_gemma":[0.4828846,0.001277544,0.4409567,0.001513453,0.000630518,0.0019505,0.003626557,0.0003771579,0.06678302],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04291396,"threshold_uncertainty_score":0.1435615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01829116646945745,"score_gpt":0.2367273536270173,"score_spread":0.2184361871575599,"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."}}