{"id":"W4407865308","doi":"10.23917/iseth.3835","title":"Exploring Differentiated Learning: A Bibliometric Examination of Research Development and Directions","year":2024,"lang":"en","type":"article","venue":"Proceeding ISETH (International Summit on Science Technology and Humanity)","topic":"Human Resource Development and Performance Evaluation","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Psychology; Mathematics education","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.02858222,0.0005422041,0.001249439,0.1286474,0.00135642,0.00855103,0.001140044,0.0005502362,0.002098298],"category_scores_gemma":[0.107334,0.0002940912,0.001361827,0.187223,0.00147267,0.007969758,0.005010812,0.0005080601,0.0006204082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003793382,"about_ca_system_score_gemma":0.01037464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005260895,"about_ca_topic_score_gemma":0.005950621,"domain_scores_codex":[0.9780879,0.003896961,0.005240137,0.001468444,0.01050811,0.0007984819],"domain_scores_gemma":[0.8849168,0.04583821,0.03002383,0.005590064,0.03150802,0.002123065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002420148,0.0001060008,0.585876,0.006657411,0.0007306286,0.0004157152,0.01065878,0.001325083,0.00104455,0.01568525,0.00936671,0.3678919],"study_design_scores_gemma":[0.00005515186,0.0004033413,0.8729644,0.005324479,0.0008119,0.001101577,0.02454592,0.004412262,0.002136732,0.01167141,0.07642319,0.0001496936],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8279742,0.04565587,0.01175904,0.007528347,0.0002854814,0.00154329,0.02185923,0.0007242578,0.08267034],"genre_scores_gemma":[0.9557158,0.01571729,0.01632227,0.0002389087,0.0002161873,0.0008283663,0.008329777,0.00008918237,0.00254221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8713526,"threshold_uncertainty_score":0.151159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3345898660764366,"score_gpt":0.4300717017715207,"score_spread":0.09548183569508406,"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."}}