{"id":"W3028733537","doi":"10.1073/pnas.1909326117","title":"Leveraging mobile phones to attain sustainable development","year":2020,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"ICT Impact and Policies","field":"Engineering","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","keywords":"Mobile phone; Disadvantaged; Empowerment; Geospatial analysis; Business; Reproductive health; Poverty; Internet privacy; Population; Economic growth; Computer science; Environmental health; Geography; Telecommunications; Economics; Medicine","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":[0.0003638,0.00006572469,0.00008948287,0.00009203581,0.0001184903,0.00002297662,0.0004168231,0.00002739574,0.00001137141],"category_scores_gemma":[0.0001594675,0.00004753159,0.00002525386,0.0007008985,0.00009479531,0.0002413048,0.00009547528,0.00007089286,0.000004053816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003796446,"about_ca_system_score_gemma":0.0000236769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003621944,"about_ca_topic_score_gemma":8.643803e-9,"domain_scores_codex":[0.9991395,0.000001102555,0.0001647409,0.00005643049,0.0004689226,0.0001692932],"domain_scores_gemma":[0.9997701,0.00003358547,0.00004942402,0.000002671485,0.0001029627,0.00004123683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001524328,0.00002570182,0.006677186,0.0007312601,0.00004364554,1.32754e-8,0.0704334,0.08347173,0.7856357,0.01892322,0.03243672,0.001606143],"study_design_scores_gemma":[0.00007339229,0.00002593002,0.01038252,0.00004163596,0.000003135925,0.000001463993,0.006938737,0.002100927,0.9615958,0.001577511,0.01714998,0.0001089717],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908928,0.00008513512,0.000007332515,0.002491793,0.00001027155,0.0001307799,0.000001530797,0.00003261866,0.006347727],"genre_scores_gemma":[0.9982705,0.000004910936,0.0007680047,0.0006542298,0.00006004659,0.00001156802,3.034284e-8,0.000004081868,0.0002266271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.17596,"threshold_uncertainty_score":0.1938282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03578375556961504,"score_gpt":0.2806838644940916,"score_spread":0.2449001089244766,"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."}}