{"id":"W6977207260","doi":"10.6084/m9.figshare.c.6822022.v1","title":"A declaration on the value of experiential measures of food and water insecurity to improve science and policies in Latin America and the Caribbean","year":2023,"lang":"en","type":"other","venue":"Figshare","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Declaration; Experiential learning; Latin Americans; Food insecurity; Food security; Water security; Scale (ratio); Value (mathematics)","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":[],"consensus_categories":[],"category_scores_codex":[0.00009874123,0.0000748354,0.0001111176,0.0001046836,0.00006771322,0.00007248242,0.0002537812,0.00002482951,0.00005800903],"category_scores_gemma":[0.0001564454,0.00004174798,0.00001368453,0.0003072984,0.00009948233,0.00004040713,0.0003147616,0.00005865779,0.000003597695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007751075,"about_ca_system_score_gemma":0.00005155832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003424698,"about_ca_topic_score_gemma":0.0001833448,"domain_scores_codex":[0.9993476,0.00003355968,0.0001030897,0.0001967511,0.0002390266,0.00008002409],"domain_scores_gemma":[0.9994406,0.000168247,0.0000767816,0.0002126664,0.00007710446,0.00002459009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006215621,0.0001663521,0.00005385257,0.0004138211,0.0001048502,0.000001036654,0.09883942,0.00037776,0.00729614,0.5974417,0.2020583,0.09318458],"study_design_scores_gemma":[0.005402272,0.002018583,0.07213216,0.006865494,0.0000801591,0.00001090622,0.002558042,0.1615849,0.07990563,0.1351678,0.5315707,0.002703406],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3639311,0.005601154,0.01547124,0.05798924,0.001366533,0.03219792,0.3560719,0.001370648,0.1660003],"genre_scores_gemma":[0.9988889,0.000006873028,0.0002521142,0.0002182564,0.00004125708,0.0002348045,0.0001533077,0.00003043885,0.0001740399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6349578,"threshold_uncertainty_score":0.1702433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0398887039568817,"score_gpt":0.2641524753121799,"score_spread":0.2242637713552982,"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."}}