{"id":"W4403740956","doi":"10.1016/j.omega.2024.103218","title":"Effect of counterfeits and fake reviews in markets for credence goods","year":2024,"lang":"en","type":"article","venue":"Omega","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Credence; Credence good; Commerce; Business; Advertising; Economics; Information asymmetry; Computer science; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004568477,0.001466748,0.002551649,0.0009285989,0.001534968,0.005509867,0.001551675,0.00421587,0.04152205],"category_scores_gemma":[0.02429816,0.0009036758,0.002262212,0.0004229703,0.002178188,0.006138712,0.002352199,0.004068012,0.001520605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003630661,"about_ca_system_score_gemma":0.002868357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01461921,"about_ca_topic_score_gemma":0.009556181,"domain_scores_codex":[0.9972863,0.001023964,0.0001042184,0.0003848643,0.000231811,0.000968773],"domain_scores_gemma":[0.9224286,0.05884947,0.009849992,0.001600756,0.002319073,0.00495213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.09439303,0.02382781,0.1777879,0.005417831,0.001902408,0.005833901,0.001835085,0.3537101,0.0341973,0.178867,0.0327629,0.08946475],"study_design_scores_gemma":[0.01200689,0.01765085,0.1222175,0.0004996104,0.002732283,0.0008499685,0.004359623,0.7445506,0.009490728,0.07650104,0.008188955,0.0009518479],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9749987,0.001152652,0.002705832,0.001494385,0.0001131995,0.0003076802,0.0007010027,0.0001175333,0.01840901],"genre_scores_gemma":[0.9946442,0.0002295911,0.0006893552,0.0001873491,0.00005895465,0.000098234,0.0001609753,0.00001389438,0.00391763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04152205,"threshold_uncertainty_score":0.1389051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01441803401884678,"score_gpt":0.2933173857222027,"score_spread":0.2788993517033559,"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."}}