{"id":"W3118606065","doi":"10.1108/jbim-12-2019-0532","title":"Assessing industry differences in marketing innovation using multi-level modeling","year":2021,"lang":"en","type":"article","venue":"Journal of Business and Industrial Marketing","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Ottawa","funders":"","keywords":"Marketing; Business; Context (archaeology); Product innovation; Competition (biology); Scale (ratio); Marketing management; Innovation management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02669443,0.0002226068,0.0006525307,0.001444306,0.0003570981,0.001350094,0.0002965224,0.0004782568,0.0001873004],"category_scores_gemma":[0.07973859,0.0001792108,0.00007066233,0.00630085,0.0000663893,0.001800947,0.0002644658,0.00137313,5.715119e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001020236,"about_ca_system_score_gemma":0.0007464319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002790915,"about_ca_topic_score_gemma":0.000009365094,"domain_scores_codex":[0.9940009,0.001182073,0.002854459,0.0003831426,0.001222213,0.0003572432],"domain_scores_gemma":[0.9909108,0.002203393,0.002240543,0.0001904564,0.004366932,0.0000879322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003458469,0.0001444127,0.5497276,0.00003249922,0.00002530917,0.0001457672,0.0002323772,0.004905136,0.01204175,0.0001059604,0.00007616146,0.4322172],"study_design_scores_gemma":[0.002993509,0.00001426285,0.4794096,0.00238823,0.0000247068,0.00039441,0.01108833,0.5026352,0.0001757708,0.0003431659,0.0001634918,0.0003693107],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9733187,0.0001385128,0.02414113,0.0006296962,0.001207496,0.00007198996,0.000002557611,0.000007609326,0.0004823324],"genre_scores_gemma":[0.9846898,0.00002039294,0.01439554,0.0001344473,0.0006249339,7.189687e-7,0.000001733495,0.00001747236,0.0001149392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.49773,"threshold_uncertainty_score":0.9996866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5160721326653742,"score_gpt":0.4098097734950751,"score_spread":0.1062623591702991,"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."}}