{"id":"W2595198204","doi":"","title":"The Effects of Reward Type on Evaluations of an Online Lucky Draw","year":2016,"lang":"en","type":"article","venue":"Journal of electronic commerce research","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Popularity; Advertising; Marketing; Business; Value (mathematics); Computer science; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004191988,0.0009042085,0.0009038294,0.0009760895,0.0007216026,0.004403161,0.0009845172,0.001814287,0.02591386],"category_scores_gemma":[0.05806797,0.0003951547,0.0009328995,0.0007442314,0.0008078634,0.002449734,0.001658604,0.002557337,0.002494806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000882939,"about_ca_system_score_gemma":0.0005229087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002004798,"about_ca_topic_score_gemma":0.002344463,"domain_scores_codex":[0.9973701,0.001046724,0.0001957398,0.0004008667,0.0007215973,0.0002650048],"domain_scores_gemma":[0.8936231,0.07935727,0.01449663,0.003397147,0.003902798,0.005223063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.04501372,0.0149117,0.8030826,0.001730018,0.001181356,0.0005777795,0.009950911,0.00386092,0.01530068,0.003880362,0.005929442,0.0945805],"study_design_scores_gemma":[0.0003095518,0.003490669,0.9851474,0.0002056366,0.0003525047,0.00009805469,0.002401551,0.003590244,0.000894451,0.00148557,0.001890164,0.0001341553],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881318,0.0002923215,0.0003682375,0.0001148154,0.00006228164,0.00009355754,0.0002544196,0.00004962368,0.01063299],"genre_scores_gemma":[0.9930357,0.000176276,0.0008280068,0.00008940239,0.00004396436,0.000218578,0.0004276391,0.00006165322,0.005118717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02591386,"threshold_uncertainty_score":0.08669049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2551085598814087,"score_gpt":0.541314260240672,"score_spread":0.2862057003592632,"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."}}