{"id":"W2570771009","doi":"10.1177/1541931215591384","title":"Guidelines and Caveats for Manipulating Expectancies in Experiments Involving Human Participants","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada","keywords":"Moderation; Rare events; Event (particle physics); Spell; Computer science; Cognitive psychology; Psychology; Data science; Risk analysis (engineering); Social psychology; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.00172436,0.0001631272,0.0002807133,0.00007371594,0.0004617297,0.0002855382,0.0003368052,0.00006551714,0.000002132687],"category_scores_gemma":[0.000826369,0.000114075,0.0001003949,0.0001751319,0.0001153651,0.0008803951,0.0004131384,0.0000865737,2.676824e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005990846,"about_ca_system_score_gemma":0.00001480702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001209313,"about_ca_topic_score_gemma":0.00003694814,"domain_scores_codex":[0.9983146,0.000008577877,0.0007877597,0.000266057,0.0003421307,0.000280885],"domain_scores_gemma":[0.9987004,0.000108715,0.0004986809,0.00007856988,0.0005201972,0.00009338291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001638309,0.00002122988,0.9221497,0.0000362307,0.00001596875,2.547346e-8,0.06363568,0.00004241936,0.008764463,0.002128652,0.003014229,0.000174997],"study_design_scores_gemma":[0.00138082,0.0001118097,0.4132553,0.000248391,0.00004447271,7.483025e-7,0.5623286,0.007323794,0.00886109,0.005272913,0.0007285378,0.0004435053],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991448,0.0001879925,0.000004651342,0.00008481859,0.00008526802,0.0002404011,0.00001000167,0.00001614204,0.0002259277],"genre_scores_gemma":[0.9982961,0.00001076552,0.001304774,0.00008148403,0.00005994518,0.00001909561,0.000001721643,0.00001086909,0.0002152182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5088944,"threshold_uncertainty_score":0.4651842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4853604369481498,"score_gpt":0.4457808396322749,"score_spread":0.03957959731587485,"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."}}