{"id":"W4281940264","doi":"10.1007/s11002-022-09635-6","title":"Marketing insights from text analysis","year":2022,"lang":"en","type":"article","venue":"Marketing Letters","topic":"Consumer Behavior in Brand Consumption and Identification","field":"Business, Management and Accounting","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; York University","funders":"","keywords":"Computer science; Variety (cybernetics); Field (mathematics); Data science; Word of mouth; Marketing research; Marketing; Artificial intelligence; Business; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001236409,0.0001657891,0.0002009535,0.0006740081,0.0008449462,0.0004418548,0.0003597673,0.00002511797,0.009311187],"category_scores_gemma":[0.0002081897,0.000187583,0.0002084665,0.001366377,0.00003870391,0.0003883686,0.000344471,0.0002313226,0.0002388558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007026374,"about_ca_system_score_gemma":0.000007370419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006690759,"about_ca_topic_score_gemma":0.00007968628,"domain_scores_codex":[0.9983038,0.0002032152,0.0003529198,0.0004639454,0.0004427385,0.0002333499],"domain_scores_gemma":[0.998993,0.0002791942,0.0002856599,0.000378055,0.00005028407,0.00001375384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005473201,0.0001766655,0.6998464,0.00007105387,0.0006042694,0.00004991387,0.0001649461,0.0004268097,0.04697882,0.000117187,0.06859829,0.1824183],"study_design_scores_gemma":[0.0002906204,3.332537e-7,0.8707268,0.000009072465,0.000540512,5.060278e-7,0.0003124134,0.003569812,0.000009639094,0.00002231109,0.1242634,0.000254629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926677,0.0001253432,0.0001130319,0.002693271,0.0006543323,0.0001426379,0.000007777753,0.0002107226,0.003385215],"genre_scores_gemma":[0.9937044,0.00000341062,0.0001075579,0.005038919,0.0003401087,0.00008291631,0.0002613347,0.00002482322,0.0004365163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1821636,"threshold_uncertainty_score":0.9915944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01390059581919982,"score_gpt":0.2082041759952505,"score_spread":0.1943035801760507,"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."}}