{"id":"W4415260891","doi":"10.1016/j.cell.2025.09.013","title":"Exploring Latin America one cell at a time","year":2025,"lang":"en","type":"article","venue":"Cell","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Institut National Du Cancer; Royal Society; Chan Zuckerberg Initiative; Wellcome Trust","keywords":"Latin Americans; Emerging technologies; The Internet; Development studies; Genomics","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":[0.0003737625,0.000396958,0.0002504868,0.0005022819,0.001518933,0.00223086,0.0004224495,0.0006512841,0.005907181],"category_scores_gemma":[0.0003990839,0.000102095,0.0002049031,0.0009641181,0.001930085,0.001573526,0.001580421,0.001399458,0.0005725583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002650915,"about_ca_system_score_gemma":0.00265088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05186445,"about_ca_topic_score_gemma":0.1190974,"domain_scores_codex":[0.9998662,0.00004413768,0.000002682114,0.00002603624,0.0000129176,0.00004799322],"domain_scores_gemma":[0.9998744,0.00002584532,0.00001849013,0.00001471997,0.00003458677,0.00003197107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004231287,0.0001658707,0.04020246,0.0008110583,0.0001274322,0.004167241,0.03477763,0.001385119,0.06779402,0.540337,0.04868567,0.2611234],"study_design_scores_gemma":[0.0000155917,0.00004171061,0.01248143,0.0003129196,0.00004203574,0.0005711528,0.03026932,0.0003060889,0.003402766,0.03756751,0.9149652,0.0000241716],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2922624,0.04232275,0.01062472,0.06764695,0.001356198,0.00005558135,0.0008141163,0.0002289651,0.5846882],"genre_scores_gemma":[0.882275,0.02858094,0.01177897,0.007580196,0.0002997459,0.00008046859,0.0005596865,0.0001193269,0.06872571],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05186445,"threshold_uncertainty_score":0.1031251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650383051493146,"score_gpt":0.2471311624011095,"score_spread":0.2306273318861781,"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."}}