{"id":"W255532472","doi":"10.29173/iasl8201","title":"Information for All: Resource Generation and Information Repackaging in Nigerian Schools","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information resource; Dilemma; Reading (process); Resource (disambiguation); Scarcity; School library; Public relations; Knowledge management; Sociology; Computer science; Political science; World Wide Web; 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":["scholarly_communication"],"category_scores_codex":[0.0008339981,0.00009937106,0.0001186596,0.0002109412,0.0003533935,0.001585613,0.0001567958,0.000101135,0.00004676422],"category_scores_gemma":[0.0009696739,0.0001026228,0.00002704791,0.000465402,0.00007198772,0.07755002,0.00005512897,0.0001258892,0.00002771355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005603682,"about_ca_system_score_gemma":0.0003595745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001276698,"about_ca_topic_score_gemma":0.0000193136,"domain_scores_codex":[0.9988126,0.00002040892,0.0004426241,0.0001107202,0.0003219423,0.0002917578],"domain_scores_gemma":[0.9987745,0.00002977329,0.0001934351,0.00005852399,0.0008189359,0.0001248223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002728826,0.00001177841,0.006398586,0.0000736665,0.000005144375,2.336716e-7,0.8196161,0.000006900084,0.0001270477,0.1202738,0.01431106,0.03914835],"study_design_scores_gemma":[0.0003601089,0.00003585706,0.003682583,0.00004777927,0.00000318018,0.000002836993,0.2895361,0.002807637,0.0005244038,0.001645751,0.7011787,0.0001751151],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9524369,0.00002705956,0.001800708,0.02683043,0.0001870538,0.0006051479,0.00004489753,0.0001227911,0.01794506],"genre_scores_gemma":[0.9886246,0.00005782635,0.001873398,0.008720526,0.000141112,0.00005952416,0.0001956797,0.000003033133,0.0003242758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6868676,"threshold_uncertainty_score":0.9994509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02251300854378291,"score_gpt":0.2818683158693726,"score_spread":0.2593553073255897,"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."}}