{"id":"W2967154792","doi":"10.29173/iasl7167","title":"Libraries on the Move: By Land, By Sea, and By Air","year":2017,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"ICT in Developing Communities","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Staffing; Developing country; Poverty; Literacy; Mobile technology; Business; Political science; Economic growth; Public relations; Mobile device; World Wide Web; Computer science; Economics","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003036362,0.0002411972,0.0001966979,0.00003825844,0.00122052,0.002517123,0.003011043,0.000105216,0.00001744021],"category_scores_gemma":[0.0002820664,0.0001739119,0.00002622673,0.0000785114,0.0004842449,0.002112039,0.001227975,0.0003727915,0.00003410503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001730671,"about_ca_system_score_gemma":0.00008033976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002039379,"about_ca_topic_score_gemma":0.000003120016,"domain_scores_codex":[0.9987556,0.00002123836,0.0001755343,0.0003352683,0.0003391656,0.0003731436],"domain_scores_gemma":[0.9987932,0.0001586929,0.0001857594,0.0004783682,0.0002846981,0.00009922681],"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":[0.00001790927,0.00004865145,0.01308743,0.00003900151,0.00002817764,0.000001311466,0.05444849,3.359783e-8,0.0002094688,0.0628352,0.8573831,0.0119012],"study_design_scores_gemma":[0.001755647,0.00109909,0.03103395,0.0008176374,0.0000314968,0.00006833005,0.02989429,0.008258785,0.06907627,0.08326525,0.7719076,0.002791704],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9218609,0.0004791172,0.001681551,0.05639296,0.0002629106,0.0003035809,0.0001629319,0.0003444167,0.01851162],"genre_scores_gemma":[0.9923169,0.0001083344,0.0005751189,0.002659394,0.00003616912,0.0000361075,0.000007855953,0.00001412346,0.004246023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08547558,"threshold_uncertainty_score":0.9985183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02276470288678265,"score_gpt":0.2386032597841595,"score_spread":0.2158385568973769,"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."}}