{"id":"W2963668529","doi":"10.1145/3219166.3219175","title":"Strategyproof Linear Regression in High Dimensions","year":2018,"lang":"en","type":"article","venue":"","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Office of Naval Research; Office of Naval Research Global; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Hyperplane; Intersection (aeronautics); Computer science; Focus (optics); Linear regression; Theoretical computer science; Mathematics; Machine learning; Combinatorics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001002511,0.00006413912,0.0001039391,0.0001425259,0.0001816677,0.00004050786,0.0002922342,0.00005241697,0.004845231],"category_scores_gemma":[0.0003902252,0.00003770408,0.00003044502,0.0008265307,0.0001571966,0.0001812492,0.0000726654,0.00008104814,0.003998219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001004254,"about_ca_system_score_gemma":0.00003032403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002859051,"about_ca_topic_score_gemma":0.00009176708,"domain_scores_codex":[0.9988112,0.0000988801,0.0003246146,0.0002907483,0.0003485516,0.0001259385],"domain_scores_gemma":[0.9989148,0.0003020011,0.00007810938,0.0004696282,0.0001661619,0.00006929254],"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":[0.00005046629,0.0001853517,0.004693821,6.052518e-7,0.000003325312,0.000002974142,0.0003455373,0.0001239779,0.007959195,0.916155,0.03213348,0.0383463],"study_design_scores_gemma":[0.0003194819,0.00008896825,0.01697102,0.00001239787,0.000002498168,0.000005329573,0.001108528,0.002748489,0.02295025,0.8960423,0.05960576,0.0001449705],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.932749,0.0000126688,0.01731531,0.002235891,0.0002428266,0.0001360566,0.000004276666,0.00006654623,0.04723739],"genre_scores_gemma":[0.9800868,0.000002296021,0.002724969,0.0002607097,0.0001332479,0.00001012257,0.000001581296,0.000003787344,0.01677649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04733776,"threshold_uncertainty_score":0.9967773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1236838744851887,"score_gpt":0.4336933010368734,"score_spread":0.3100094265516847,"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."}}