{"id":"W4229000435","doi":"10.1371/journal.pone.0268110","title":"Becoming metrics literate: An analysis of brief videos that teach about the h-index","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Uniformed Services University of the Health Sciences; Social Sciences and Humanities Research Council of Canada; U.S. Department of Defense","keywords":"Index (typography); Computer science; Medicine; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.004509581,0.0003261244,0.0002077131,0.003825308,0.0008870161,0.001664717,0.0004405483,0.0005928727,0.002933332],"category_scores_gemma":[0.04906903,0.0001606279,0.0002551954,0.002156281,0.0007727046,0.001661025,0.001000188,0.0007896955,0.0005456128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00223669,"about_ca_system_score_gemma":0.001621344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005818026,"about_ca_topic_score_gemma":0.01172335,"domain_scores_codex":[0.9979681,0.0009801463,0.0001526357,0.0001487379,0.0005535947,0.0001967179],"domain_scores_gemma":[0.9556025,0.03235887,0.003889159,0.0006399332,0.006236976,0.001272686],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001005922,0.0009002652,0.1360019,0.004938323,0.00008951631,0.003274838,0.2864232,0.0006040211,0.01236974,0.003446619,0.04681326,0.5041324],"study_design_scores_gemma":[0.00006199189,0.001230231,0.5803033,0.005117889,0.000119711,0.002342559,0.2147801,0.003453417,0.006442345,0.002301463,0.1836303,0.0002167292],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9616337,0.001110423,0.007325563,0.001587127,0.0002299121,0.002145179,0.00418881,0.0001810824,0.02159811],"genre_scores_gemma":[0.9576647,0.002248547,0.02360198,0.0009522962,0.0002340062,0.002799915,0.003858312,0.0001822691,0.008458008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9961747,"threshold_uncertainty_score":0.02384925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6494989492659259,"score_gpt":0.5132583067132458,"score_spread":0.1362406425526801,"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."}}