{"id":"W3122491397","doi":"","title":"Benefits Segmentation of Visitors to Latin America","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Latin Americans; Tourism; Demographics; Accommodation; Segmentation; Marketing; Business; Market segmentation; Geography; Political science; Computer science; Artificial intelligence; Sociology; Psychology","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":[0.0004484071,0.0001868802,0.0001953434,0.0008871893,0.001591011,0.001685503,0.0002282225,0.0003338862,0.004662154],"category_scores_gemma":[0.001598014,0.0001109147,0.0002253736,0.001124171,0.0007036898,0.0007922575,0.001678061,0.00043496,0.0002218287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001664156,"about_ca_system_score_gemma":0.0009590289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02602479,"about_ca_topic_score_gemma":0.06390116,"domain_scores_codex":[0.9995959,0.0001386584,0.00001104318,0.00003055105,0.00006899214,0.000154754],"domain_scores_gemma":[0.9995074,0.0001162323,0.0001057267,0.00003112458,0.0001191949,0.0001203762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008537952,0.00025344,0.6957548,0.0002809408,0.00007093784,0.001704456,0.1375722,0.0008892733,0.004381569,0.02121518,0.005058784,0.1319646],"study_design_scores_gemma":[0.00001671464,0.0001111488,0.7548035,0.0002060801,0.00002531242,0.0005181806,0.2141459,0.0006628162,0.0003631576,0.00386337,0.02525862,0.00002523972],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747956,0.0002576867,0.0002480942,0.0004742521,0.000008514321,0.00002226558,0.00007663613,0.000004757563,0.0241123],"genre_scores_gemma":[0.9972549,0.0001989063,0.0002348671,0.00007763428,0.000004889975,0.00002166345,0.00007695942,0.00000490814,0.002125254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02602479,"threshold_uncertainty_score":0.05174661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01442541953003325,"score_gpt":0.3198006283261972,"score_spread":0.305375208796164,"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."}}