{"id":"W2951559990","doi":"10.29173/iasl7133","title":"Samples of Applied Interdisciplinary Library Lessons","year":2018,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Diverse Educational Innovations Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subject (documents); Field (mathematics); School library; Library science; Work (physics); Sample (material); Computer science; Sociology; Mathematics education; Engineering; Psychology; Mathematics; Chemistry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008268447,0.0001111611,0.0001440389,0.00002706639,0.0002266297,0.00006892782,0.0003156681,0.00005181321,0.0009519437],"category_scores_gemma":[0.00003772273,0.00004806268,0.00003413641,0.0004918535,0.0003297055,0.0004000067,0.000465216,0.00007155359,0.0000763378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007725584,"about_ca_system_score_gemma":0.00002328906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001564214,"about_ca_topic_score_gemma":0.00001152733,"domain_scores_codex":[0.9992281,0.00000270182,0.0001976241,0.0002353925,0.0001569752,0.0001791661],"domain_scores_gemma":[0.9991781,0.00005909978,0.0001198378,0.00002390579,0.0005737537,0.00004538028],"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":[0.0002694262,0.0005531998,0.04703894,0.00007350965,0.0001117732,6.378754e-7,0.136662,1.24534e-7,0.1023113,0.4568945,0.1374711,0.1186135],"study_design_scores_gemma":[0.0001503633,0.0005738238,0.5288661,0.0001088397,0.00002372183,0.000004162789,0.3284225,0.00001537441,0.02968952,0.06996378,0.04174933,0.0004325206],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9418834,0.00001056428,0.00000248109,0.006225489,0.00009823761,0.000105346,0.0001241036,0.0000750181,0.05147531],"genre_scores_gemma":[0.9981539,0.000008058837,0.0005486494,0.0001962288,0.0003597403,0.00002335268,0.00003812966,9.814078e-7,0.0006709562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4818271,"threshold_uncertainty_score":0.9999613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06154439645072976,"score_gpt":0.2870288035007892,"score_spread":0.2254844070500594,"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."}}