{"id":"W4242737713","doi":"10.5539/gjhs.v11n2p148","title":"Reviewer Acknowledgements for Global Journal of Health Science, Vol. 11, No. 2","year":2019,"lang":"en","type":"article","venue":"Global Journal of Health Science","topic":"Academic Publishing and Open Access","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health science; Library science; Global health; Political science; Engineering ethics; Medicine; Medical education; Health care; Computer science; Engineering; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.1102713,0.0002760989,0.001391942,0.0007047682,0.001202289,0.001941707,0.01147976,0.00009926767,0.0002166227],"category_scores_gemma":[0.09226419,0.0001775613,0.0003597351,0.008027135,0.001340637,0.008375674,0.0007914136,0.0005401734,0.0003167256],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002346853,"about_ca_system_score_gemma":0.02346928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000446685,"about_ca_topic_score_gemma":0.00001386943,"domain_scores_codex":[0.9836175,0.0003094947,0.004795238,0.0007348682,0.009002331,0.001540579],"domain_scores_gemma":[0.9066929,0.0002939139,0.009857282,0.0008364327,0.08070163,0.001617853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004894602,0.0001055923,0.2586882,0.0000583489,0.00000771552,0.0000017163,0.00005946011,0.00008154917,0.000008912696,0.0007216323,0.6198055,0.1204125],"study_design_scores_gemma":[0.002580686,0.001970381,0.2585005,0.001420883,0.00001965659,0.0004705373,0.001117384,0.000845483,0.00004589496,0.02057751,0.7120453,0.0004058283],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6906381,0.02576349,0.02354311,0.01716528,0.2308815,0.002364762,0.0001404417,0.00003333732,0.009470074],"genre_scores_gemma":[0.9597364,0.001507678,0.02197228,0.010856,0.004529522,0.000003871596,0.000001128346,0.000018313,0.001374793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2690984,"threshold_uncertainty_score":0.9990944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08955972422465991,"score_gpt":0.4764004601979092,"score_spread":0.3868407359732493,"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."}}