{"id":"W286111093","doi":"10.29173/slw7067","title":"Editorial: Learning from Our Past","year":2000,"lang":"en","type":"editorial","venue":"School Libraries Worldwide","topic":"Library Science and Administration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Theme (computing); Field (mathematics); Library science; School library; Sociology; Engineering ethics; Computer science; World Wide Web; Engineering","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":[0.007222598,0.004152697,0.002667458,0.005156049,0.00531286,0.01159426,0.00375102,0.01395938,0.01790247],"category_scores_gemma":[0.03671059,0.001002975,0.001824378,0.002490836,0.003473958,0.006013906,0.001602611,0.0165145,0.01337793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003926986,"about_ca_system_score_gemma":0.004797678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001694163,"about_ca_topic_score_gemma":0.004509756,"domain_scores_codex":[0.9936098,0.0009214674,0.0006231251,0.0008029543,0.003662935,0.000379686],"domain_scores_gemma":[0.9715629,0.006974129,0.001533723,0.001016286,0.01422127,0.004691835],"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":[0.00001589701,0.000009557175,0.00002230124,0.0001045197,0.000004963873,0.00008938097,0.0000239389,0.00001389134,0.0000288603,0.0002046042,0.9961466,0.003335425],"study_design_scores_gemma":[0.00002955357,0.00002925696,0.000250626,0.0003617182,0.00002356499,0.0002628593,0.0001291368,0.00009109297,0.000110905,0.00071026,0.997985,0.00001595404],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00003277003,0.001384001,0.0000629865,0.02328039,0.9734075,0.00001849562,0.00001884324,0.00004370506,0.001751338],"genre_scores_gemma":[0.0008800691,0.002795133,0.0001699627,0.02534666,0.9490564,0.00003757409,0.00004390026,0.00006633042,0.02160396],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01790247,"threshold_uncertainty_score":0.05988973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01299187050790181,"score_gpt":0.2723958678091274,"score_spread":0.2594039973012256,"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."}}