{"id":"W2066900428","doi":"10.1509/jmr.13.0437","title":"Product Customization via Starting Solutions","year":2014,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Color perception and design","field":"Psychology","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Personalization; Product (mathematics); Computer science; Dilemma; Offset (computer science); Mathematics; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.002018766,0.000755753,0.0002963411,0.001176324,0.0004313054,0.002101411,0.001088577,0.0009074918,0.009247497],"category_scores_gemma":[0.009939572,0.0004005347,0.0009812126,0.0008600025,0.001120812,0.003480602,0.00187746,0.00122334,0.001751138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007751967,"about_ca_system_score_gemma":0.0008981075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008050727,"about_ca_topic_score_gemma":0.001476569,"domain_scores_codex":[0.9978049,0.0009161459,0.0001174508,0.0003555074,0.0006849563,0.0001211459],"domain_scores_gemma":[0.9947087,0.002104784,0.0006788975,0.001692572,0.0006027619,0.0002124201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000577171,0.001173525,0.02425829,0.001056169,0.0001753843,0.0005327432,0.004989326,0.01210707,0.04431101,0.1256493,0.006475513,0.7786945],"study_design_scores_gemma":[0.000622826,0.005732295,0.08960855,0.001326632,0.000648624,0.004347998,0.007147085,0.09327102,0.08807481,0.3163992,0.3923319,0.0004891175],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5888922,0.0009278388,0.2614849,0.0009859749,0.0001044055,0.001275788,0.0003059054,0.001816958,0.1442061],"genre_scores_gemma":[0.7652463,0.0006913549,0.2196143,0.0003812553,0.00003326283,0.0004311167,0.0003567969,0.0002240355,0.01302161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009247497,"threshold_uncertainty_score":0.030936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1467979263148156,"score_gpt":0.4359644360736317,"score_spread":0.2891665097588161,"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."}}