{"id":"W3121881764","doi":"10.5167/uzh-174509","title":"Perceiving prospects properly","year":2016,"lang":"en","type":"preprint","venue":"Zurich Open Repository and Archive (University of Zurich)","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Status quo; Curse; Action (physics); Perception; Noise (video); Key (lock); Status quo bias; Mathematical economics; Winner's curse; Computer science; Microeconomics; Econometrics; Economics; Psychology; Artificial intelligence; Computer security; Common value auction; Sociology","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":[],"consensus_categories":[],"category_scores_codex":[0.002120684,0.0002667152,0.0005858442,0.0002768951,0.0008581652,0.0004167955,0.003089987,0.0001774385,0.0001001022],"category_scores_gemma":[0.0001910467,0.0002162838,0.0001857016,0.0002744393,0.0005360977,0.00040765,0.006526356,0.0004148011,0.00003932297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004754631,"about_ca_system_score_gemma":0.0002267698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052958,"about_ca_topic_score_gemma":0.00009384315,"domain_scores_codex":[0.9969935,0.0005713117,0.0004060923,0.001126886,0.0006335245,0.0002686269],"domain_scores_gemma":[0.9965365,0.0009721774,0.000758191,0.001206651,0.0003265554,0.000199952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001144117,0.001783416,0.08961952,0.0008906739,0.0007763532,0.0008189169,0.0539414,0.0001726954,0.08480538,0.1310777,0.4846696,0.1503002],"study_design_scores_gemma":[0.001299103,0.0007250555,0.1848796,0.001951937,0.0002580425,0.0002207906,0.003964962,0.003348643,0.001938151,0.6652655,0.1343989,0.001749367],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5981949,0.0002940934,0.1340324,0.002245322,0.0004365499,0.003140701,0.0002909927,0.0002610811,0.2611039],"genre_scores_gemma":[0.9198794,0.00007581367,0.0583238,0.00002844643,0.0001031272,0.000007016636,0.00001259498,0.00002354857,0.02154624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5341877,"threshold_uncertainty_score":0.8819797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07831609328193978,"score_gpt":0.3173156876215828,"score_spread":0.238999594339643,"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."}}