{"id":"W4387172486","doi":"10.1177/00472875231199233","title":"Revisiting and Extending: “Who Should You Market to in a Crisis? Examining Plog’s Model During the COVID-19 Pandemic”","year":2023,"lang":"en","type":"article","venue":"Journal of Travel Research","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Context (archaeology); Value (mathematics); Psychology; Data collection; Survey research; Sociology; Geography; Applied psychology; Social science; Virology; Mathematics; Medicine; Statistics","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03875489,0.000129345,0.0003318423,0.001586431,0.001207807,0.0005077642,0.001160124,0.0001334945,0.0001678323],"category_scores_gemma":[0.01591811,0.0001005022,0.00008282378,0.0020353,0.0003712548,0.0005413179,0.0006114272,0.001598998,0.00002081554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007393769,"about_ca_system_score_gemma":0.0009025968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001503929,"about_ca_topic_score_gemma":0.0004196299,"domain_scores_codex":[0.993452,0.001512509,0.0005239989,0.0003322963,0.003018065,0.001161201],"domain_scores_gemma":[0.9957445,0.002624972,0.0001390808,0.000249228,0.0004242442,0.0008180045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00296082,0.0003027509,0.4294401,0.001017087,0.0003726858,0.01470919,0.24033,0.01132117,0.01663269,0.01483427,0.2295388,0.03854049],"study_design_scores_gemma":[0.003826289,0.0005112032,0.3886278,0.001041568,0.00003941681,0.0002589294,0.5446386,0.01395563,0.0002165181,0.02653543,0.01954678,0.000801887],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9341578,0.0003438032,0.0001324253,0.04968462,0.00007911406,0.0004664129,0.000007335808,0.00003027764,0.01509817],"genre_scores_gemma":[0.9890404,0.002426184,0.0002776607,0.0002289403,0.000553561,0.00001429066,1.989048e-7,0.00002521127,0.007433528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3043086,"threshold_uncertainty_score":0.9923713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4193961542173614,"score_gpt":0.5063924718918441,"score_spread":0.08699631767448274,"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."}}