{"id":"W2187131105","doi":"10.3968/7812","title":"Analysis on Government Guarantees for Public Library Resource Construction","year":2015,"lang":"en","type":"article","venue":"Studies in literature and language","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Premise; Institution; Business; Resource (disambiguation); Incentive; Function (biology); Investment (military); Public administration; Finance; Public capital; Public welfare; Public finance; Economics; Public relations; Public investment; Political science; Economic policy; Market economy; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005967268,0.000217341,0.0003995304,0.002643199,0.003055669,0.006881476,0.0009655508,0.002494398,0.01296417],"category_scores_gemma":[0.02803488,0.0002664035,0.0007944139,0.003207262,0.005648951,0.00489194,0.002713911,0.002766889,0.0006805028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009866081,"about_ca_system_score_gemma":0.01462918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01739924,"about_ca_topic_score_gemma":0.01527124,"domain_scores_codex":[0.9910462,0.002695715,0.0003512283,0.0004467436,0.003085082,0.002375058],"domain_scores_gemma":[0.9781855,0.01307738,0.003056347,0.001562321,0.003522767,0.000595695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002611549,0.00001566029,0.00259518,0.00004042355,0.00000725389,0.00008885496,0.0007095792,0.0007705319,0.00005512312,0.9885876,0.002311141,0.004792486],"study_design_scores_gemma":[0.0000590292,0.00008816236,0.02944423,0.0008248492,0.0001549821,0.0002940123,0.0128322,0.006882238,0.001212297,0.7935132,0.1546357,0.00005897794],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2491355,0.002849004,0.01236347,0.04313177,0.0001611117,0.0001087399,0.0004939124,0.00009052652,0.6916659],"genre_scores_gemma":[0.9875014,0.0006128094,0.0005608277,0.0007659066,0.0000667072,0.00003809618,0.00007978014,0.00001472719,0.0103596],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01739924,"threshold_uncertainty_score":0.07158369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03074784293197467,"score_gpt":0.3205077283071939,"score_spread":0.2897598853752192,"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."}}