{"id":"W4403619575","doi":"10.1057/s41267-024-00736-0","title":"How to intelligently embrace generative AI: the first guardrails for the use of GenAI in IB research","year":2024,"lang":"en","type":"article","venue":"Journal of International Business Studies","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Generative grammar; International business; Economics; Epistemology; Management; Cognitive science; Psychology; Artificial intelligence; Philosophy; 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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001601931,0.0001791038,0.0002925014,0.0007517593,0.0002651061,0.001203406,0.000972881,0.00004570892,0.00003637826],"category_scores_gemma":[0.004611986,0.0000907993,0.0001368028,0.001601297,0.0002661626,0.002152778,0.0005203514,0.0003351824,0.0000187756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000114116,"about_ca_system_score_gemma":0.00008503792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001631949,"about_ca_topic_score_gemma":0.0006747827,"domain_scores_codex":[0.9981019,0.00002254998,0.0005919437,0.000219941,0.0008140918,0.0002495411],"domain_scores_gemma":[0.9917728,0.001562726,0.0002781171,0.0002140805,0.006162984,0.000009338607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001319434,0.0004169337,0.0110551,0.003057312,0.002550429,0.0001276653,0.003447033,0.01694055,0.001609893,0.1067547,0.801012,0.05170894],"study_design_scores_gemma":[0.0001777512,0.00002531601,0.009849315,0.001377267,0.00007562395,0.00002041663,0.002186367,0.006056789,0.0006273958,0.00343648,0.9760166,0.0001506803],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0828502,0.02375898,0.08261777,0.7969,0.01202065,0.001426641,0.00007958823,0.00003369513,0.0003125105],"genre_scores_gemma":[0.9853965,0.003791832,0.0007362615,0.003406369,0.005006615,0.00009721431,0.000008627297,0.00003738713,0.001519168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9025463,"threshold_uncertainty_score":0.9998335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3432117465221299,"score_gpt":0.4225430340817463,"score_spread":0.07933128755961638,"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."}}