{"id":"W2616895443","doi":"10.5958/2249-3182.2016.00008.3","title":"Greening libraries: India vs International Scenario","year":2016,"lang":"en","type":"article","venue":"Gyankosh- The Journal of Library and Information Management","topic":"Library Science and Administration","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Shastri Indo-Canadian Institute","funders":"","keywords":"Greening; Library science; Business; Geography; Political science; Computer science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005960439,0.00006643535,0.00007370734,0.0001979658,0.0003548912,0.0004644897,0.0004947298,0.00003365689,0.0005952295],"category_scores_gemma":[0.00003240585,0.00003574029,0.00003910177,0.0002423431,0.000181926,0.05119369,0.0001204057,0.00007319568,0.00001809631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009629533,"about_ca_system_score_gemma":0.00009457901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000197645,"about_ca_topic_score_gemma":3.319068e-7,"domain_scores_codex":[0.9989288,0.00009615429,0.0003781285,0.00004220443,0.0004168915,0.0001377899],"domain_scores_gemma":[0.9993337,0.0001111525,0.0003592562,0.00008210514,0.0000229744,0.00009075183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001927402,0.00002051974,0.01180083,0.00001667101,0.00006406791,0.000005437813,0.01270886,0.00001291073,0.00001189445,0.844518,0.03649259,0.09415545],"study_design_scores_gemma":[0.0003404922,0.00008054662,0.02146224,0.00006069306,0.00001197852,0.000007239217,0.005948848,0.00002150608,0.0001162698,0.005909468,0.9659696,0.00007108707],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09667028,0.0001534218,0.008401814,0.2725657,0.002050203,0.0004498983,0.00001873695,0.00009752299,0.6195924],"genre_scores_gemma":[0.9766247,0.004157574,0.002609378,0.009773131,0.0004819344,0.000002184353,0.000007987404,0.0000049724,0.006338124],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.929477,"threshold_uncertainty_score":0.9620768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01089133013185615,"score_gpt":0.2303980169192549,"score_spread":0.2195066867873988,"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."}}