{"id":"W4404795261","doi":"10.59876/a-n585-amt9","title":"Analyse par classes latentes de l’intention d’utilisation future d’une application mobile de santé publique concernant la COVID-19","year":2024,"lang":"en","type":"article","venue":"Management international","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Computer science; Political science; Medicine; Infectious disease (medical specialty)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0114077,0.001108975,0.0009238533,0.001667176,0.001036373,0.005329244,0.001082975,0.001499751,0.01043374],"category_scores_gemma":[0.02490007,0.0006255473,0.003268552,0.001515063,0.001643466,0.002921532,0.002058927,0.003796709,0.001213652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002305098,"about_ca_system_score_gemma":0.001802428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02792515,"about_ca_topic_score_gemma":0.01245905,"domain_scores_codex":[0.9938655,0.003634949,0.0003171876,0.0008358581,0.0005340502,0.0008123607],"domain_scores_gemma":[0.9655678,0.02735615,0.003566017,0.001593577,0.001114478,0.0008019229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006677879,0.0009195578,0.9617041,0.00009093072,0.0008510366,0.00009103553,0.005513155,0.003253156,0.0003361036,0.007087097,0.000908751,0.01857731],"study_design_scores_gemma":[0.00007999389,0.0005127737,0.8572637,0.0002158531,0.0003139914,0.0001386281,0.008025617,0.1238081,0.0004515069,0.006617928,0.002490127,0.00008165608],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838027,0.0001590141,0.01157016,0.0008267353,0.00004205599,0.0001677294,0.001435197,0.00004759441,0.001948828],"genre_scores_gemma":[0.9942247,0.0001156747,0.002448755,0.0000250796,0.00002363121,0.0003683496,0.001533449,0.00001454765,0.001245877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02792515,"threshold_uncertainty_score":0.06033045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07946485890617909,"score_gpt":0.4098978405639316,"score_spread":0.3304329816577525,"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."}}