{"id":"W7135158247","doi":"","title":"Exploration de biais cognitifs chez les consommateurs lors de l’utilisation de l’intelligence artificielle en tourisme : influence sur le processus décisionnel. Présenté au congrès de l’Association des sciences administratives du Canada (ASAC 2024)","year":2024,"lang":"fr","type":"article","venue":"Archipelago (University of Quebec in Montreal)","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Order (exchange); Public policy; Tourism","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":[0.003693283,0.0003815895,0.0003667874,0.0008949375,0.001529983,0.00512768,0.0006453693,0.001086588,0.00843942],"category_scores_gemma":[0.01996893,0.000324541,0.0004115168,0.0006053795,0.001520626,0.001932131,0.00156166,0.001536875,0.0007402978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001816635,"about_ca_system_score_gemma":0.002902414,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06218059,"about_ca_topic_score_gemma":0.084561,"domain_scores_codex":[0.9982914,0.0006337787,0.00005835639,0.0002347548,0.000458054,0.0003236497],"domain_scores_gemma":[0.9861954,0.006786154,0.002251729,0.0005359711,0.002587279,0.001643557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009809311,0.0007836265,0.7659734,0.0003552761,0.0002301252,0.0007605855,0.1116408,0.0006966528,0.005937192,0.003058094,0.002306913,0.1072763],"study_design_scores_gemma":[0.00001875409,0.0002880367,0.9363911,0.0001470076,0.0001011252,0.000142341,0.05321994,0.001551338,0.001113305,0.001950724,0.005024647,0.00005173072],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908029,0.0005505029,0.0006142484,0.0007249701,0.00002287449,0.00003197043,0.00004963322,0.00001106923,0.007191832],"genre_scores_gemma":[0.9950951,0.0002981983,0.0004058332,0.0001241442,0.000009613719,0.00002675295,0.00006206388,0.00001099184,0.003967253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9378194,"threshold_uncertainty_score":0.1236373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03971692202793165,"score_gpt":0.2585560499496686,"score_spread":0.218839127921737,"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."}}