{"id":"W6950513800","doi":"10.5281/zenodo.8371197","title":"STI Special Session: Metrics Literacy","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Session (web analytics); Work (physics); Information literacy; Bibliometrics; Higher education","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005437256,0.001807267,0.001406983,0.001792649,0.00304185,0.008619462,0.001655432,0.004244964,0.6322352],"category_scores_gemma":[0.006475894,0.0007235866,0.001862066,0.001205646,0.000642518,0.004601126,0.007402611,0.006591998,0.4124838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002783245,"about_ca_system_score_gemma":0.003517699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001712416,"about_ca_topic_score_gemma":0.005027307,"domain_scores_codex":[0.9980635,0.0003169477,0.00009849446,0.0002869745,0.0007162171,0.0005178089],"domain_scores_gemma":[0.991635,0.0006514613,0.0002660615,0.0003495415,0.0029626,0.004135271],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006360012,0.0000670138,0.0001006466,0.00006534404,0.000002278468,0.00002974247,0.00004479849,0.00001742145,0.0002886631,0.0004529771,0.9856736,0.01319387],"study_design_scores_gemma":[0.00002996404,0.0001513311,0.001255718,0.0001698869,0.000004090658,0.00007581751,0.0001697596,0.000131779,0.0002415897,0.0008897881,0.9968621,0.00001808656],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004382516,0.003995831,0.006615732,0.06053602,0.1113059,0.002022724,0.007536588,0.007392745,0.7962119],"genre_scores_gemma":[0.007662473,0.001215477,0.001987111,0.008047664,0.01998225,0.0008294073,0.005373453,0.002248456,0.9526536],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9982073,"threshold_uncertainty_score":0.5245719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1064665575089869,"score_gpt":0.3332072930145986,"score_spread":0.2267407355056117,"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."}}