{"id":"W2985583291","doi":"","title":"Assessing Response Format Effects on the Scaling of Marketing Stimuli","year":2014,"lang":"en","type":"article","venue":"Digital Commons - Lingnan (Lingnan University)","topic":"Behavioral and Psychological Studies","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Marketing; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2286112,0.00236787,0.001288527,0.002886394,0.001513493,0.002833999,0.001677048,0.002845777,0.007468847],"category_scores_gemma":[0.5639257,0.001035494,0.002761033,0.003702051,0.003258595,0.002812767,0.003045552,0.002649623,0.001685462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001361028,"about_ca_system_score_gemma":0.001048146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004272542,"about_ca_topic_score_gemma":0.0005169035,"domain_scores_codex":[0.6914581,0.2418131,0.02806981,0.009751428,0.02708713,0.001820402],"domain_scores_gemma":[0.1604055,0.7582828,0.01931271,0.02796463,0.03337791,0.0006564831],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.03623047,0.01104247,0.1760835,0.008836778,0.002146249,0.001043713,0.04303065,0.007907968,0.09016907,0.02161248,0.01343053,0.5884662],"study_design_scores_gemma":[0.00728582,0.05217328,0.6310966,0.006134451,0.003389776,0.001963436,0.01342197,0.04127013,0.1607229,0.02778577,0.05348102,0.001274791],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7084466,0.001233381,0.2303735,0.001407209,0.002438564,0.02908581,0.001015023,0.00147699,0.02452293],"genre_scores_gemma":[0.7079179,0.000622701,0.243665,0.00165119,0.000486096,0.04020049,0.001071943,0.001123897,0.003260741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7713888,"threshold_uncertainty_score":0.9512597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1270496860002254,"score_gpt":0.3053613087808559,"score_spread":0.1783116227806306,"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."}}