{"id":"W7131648449","doi":"10.5281/zenodo.18778721","title":"Telehealth in Sierra Leone: Accessibility and Impact on Rural Populations","year":2003,"lang":"en","type":"article","venue":"Open MIND","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Telehealth; Telemedicine; Rural area; Sample (material); Investment (military); The Internet; Health care; Focus group; Rural health","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":[0.001535087,0.0002549454,0.0002542783,0.0007853751,0.000574675,0.0007865158,0.0002917192,0.0003204415,0.001374899],"category_scores_gemma":[0.006006715,0.0001795968,0.0002261987,0.0006571346,0.0006224579,0.0005851333,0.001191377,0.0004078193,0.0000659537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005929012,"about_ca_system_score_gemma":0.0007871073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03045672,"about_ca_topic_score_gemma":0.04977019,"domain_scores_codex":[0.9989246,0.0007583213,0.00003125705,0.00005913444,0.00005951825,0.0001672091],"domain_scores_gemma":[0.998271,0.001045053,0.000335205,0.00005626788,0.0001243589,0.0001681046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003778671,0.0009472014,0.9206242,0.0003257614,0.0001072883,0.001800633,0.01618415,0.001002951,0.0008099042,0.0007019596,0.0005499633,0.05656819],"study_design_scores_gemma":[0.00008587458,0.001241731,0.9705815,0.0002035502,0.00009300739,0.0009293549,0.02265346,0.001286733,0.0003060211,0.000416052,0.002188451,0.00001422324],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988432,0.0001770349,0.00005483474,0.0001398247,0.000001928301,0.00002265927,0.00003162633,0.00000168438,0.0007271979],"genre_scores_gemma":[0.999318,0.0002412311,0.0001097406,0.00003733184,0.000004809601,0.00003594194,0.0000329143,8.079944e-7,0.0002192771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03045672,"threshold_uncertainty_score":0.06055892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.107073106681058,"score_gpt":0.4700023172835171,"score_spread":0.3629292106024591,"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."}}