{"id":"W2912780949","doi":"10.1080/25729861.2018.1532779","title":"Disentangling war and disease in post-conflict Colombia beyond technoscientific peacemaking","year":2019,"lang":"en","type":"article","venue":"Tapuya Latin American Science Technology and Society","topic":"Global Security and Public Health","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Connaught Fund; University of Toronto; York University; Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)","keywords":"Technoscience; Peacemaking; Biomedicine; Context (archaeology); Sociology; Political science; Citizen journalism; Political economy; Environmental ethics; Social science; Law; History","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["sts"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["sts"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002206739,0.0004673947,0.0003690425,0.002277134,0.008202017,0.01284563,0.0005804551,0.001380879,0.003412742],"category_scores_gemma":[0.00305445,0.0001859061,0.0002204215,0.001537508,0.02166811,0.007248813,0.00653094,0.002706632,0.0001637358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01377115,"about_ca_system_score_gemma":0.006020701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03748047,"about_ca_topic_score_gemma":0.06116733,"domain_scores_codex":[0.9980552,0.001081472,0.00004951249,0.0001649527,0.0001798532,0.0004690145],"domain_scores_gemma":[0.9979517,0.001193073,0.0003949507,0.0001268446,0.0001262523,0.0002072354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001194482,0.00005809335,0.007015614,0.0004025374,0.00001500967,0.001266432,0.4224857,0.0004084824,0.0009547119,0.5216184,0.003109114,0.04254647],"study_design_scores_gemma":[0.00002042506,0.00008080333,0.01713715,0.001074951,0.00003017955,0.0006944256,0.4918168,0.0004841602,0.001009888,0.09165332,0.3959247,0.00007332383],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4650794,0.04091893,0.007635856,0.0345554,0.0005909263,0.00009154134,0.0001428333,0.00006627727,0.4509188],"genre_scores_gemma":[0.9909888,0.003902826,0.0005017758,0.0008008378,0.00005684677,0.00002428559,0.00002661777,0.00001403364,0.003683984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.991798,"threshold_uncertainty_score":0.09991711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009175024810440373,"score_gpt":0.3002951040496901,"score_spread":0.2911200792392498,"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."}}