{"id":"W2578416181","doi":"10.2139/ssrn.2889388","title":"Exit, Tweets, and Loyalty","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Loyalty; Business; Advertising; Internet privacy; Marketing; Computer science","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":[0.001078082,0.0002615167,0.0002814348,0.001187638,0.001367658,0.003897267,0.0004117606,0.002014316,0.01434118],"category_scores_gemma":[0.01053944,0.000284246,0.0003562559,0.0009270188,0.001177615,0.002413069,0.001540787,0.002934702,0.001759046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004224821,"about_ca_system_score_gemma":0.0004132113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004008237,"about_ca_topic_score_gemma":0.007191176,"domain_scores_codex":[0.9993889,0.0002169591,0.00004085189,0.00006594497,0.0001025808,0.0001846742],"domain_scores_gemma":[0.9876253,0.005154741,0.003527792,0.0003624993,0.0005900583,0.002739585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008948445,0.001506759,0.98037,0.00003928968,0.0001367346,0.0001475578,0.001637035,0.0002424748,0.0002303304,0.002499233,0.002080787,0.01021489],"study_design_scores_gemma":[0.0000358939,0.0002107525,0.9875266,0.00004624887,0.0001168402,0.0001181763,0.006239428,0.0007559365,0.0001239746,0.002979627,0.001815773,0.00003076839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872674,0.0002503795,0.00007979989,0.001209781,0.00004689503,0.000007823147,0.0002589023,0.000008120291,0.01087091],"genre_scores_gemma":[0.9953889,0.0001386734,0.00004315332,0.000212656,0.00007870704,0.000007748631,0.0002660833,0.000006209395,0.00385794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01434118,"threshold_uncertainty_score":0.04797602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007973685537660832,"score_gpt":0.263354320624153,"score_spread":0.2553806350864922,"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."}}