{"id":"W4246824481","doi":"10.1145/3144722.3144723","title":"Editor's introduction","year":2017,"lang":"en","type":"article","venue":"ACM SIGecom Exchanges","topic":"Economic Policies and Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Matching (statistics); Computer science; Position (finance); Mechanism (biology); Information retrieval; Mathematical economics; Economics; Mathematics; Epistemology; Statistics; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003270049,0.0001328622,0.0002826671,0.0001104475,0.0004130732,0.0002874622,0.000783118,0.00009351594,0.001141825],"category_scores_gemma":[0.0008512558,0.0001535737,0.00007976803,0.00002566276,0.0000861114,0.0005764366,0.0002789923,0.0001089868,0.002263318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007725207,"about_ca_system_score_gemma":0.000007705676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008173358,"about_ca_topic_score_gemma":0.0001325672,"domain_scores_codex":[0.9990356,0.00000528384,0.0002756068,0.0003264941,0.00001839683,0.0003385967],"domain_scores_gemma":[0.9979318,0.00003280605,0.0004147245,0.001502011,0.00001624489,0.0001023955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000102513,0.00005275503,0.03829816,0.00002176074,0.00005781705,0.000001502284,0.000537332,0.000005764909,0.00007761781,0.0780236,0.8761142,0.006799282],"study_design_scores_gemma":[0.0002496027,0.00005087322,0.08627648,0.000003995749,0.000002617584,0.000002690078,0.00004483622,0.0000617238,0.0002803987,0.04023943,0.8725895,0.0001978161],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6006588,0.004184108,0.0002786433,0.1502289,0.05920105,0.0004423322,0.0003158598,0.0002202276,0.1844702],"genre_scores_gemma":[0.9573348,0.0007401739,0.0003636316,0.0006584608,0.03397017,0.00002083852,0.0000134169,0.00003098354,0.006867538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.356676,"threshold_uncertainty_score":0.9997712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05311468100512562,"score_gpt":0.2597255573032936,"score_spread":0.2066108762981679,"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."}}