{"id":"W4401535050","doi":"10.2139/ssrn.4912473","title":"MAKING SPACE FOR ONLINE RESEARCH EXPERIMENTS IN LAW SCHOOL COURSES *","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University; Toronto Metropolitan University","funders":"","keywords":"Space (punctuation); Mathematics education; Law; Sociology; Political science; Psychology; Computer science","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"],"consensus_categories":[],"category_scores_codex":[0.02597694,0.0006919654,0.0007943976,0.001493486,0.003558405,0.009875821,0.002564976,0.003464385,0.1147338],"category_scores_gemma":[0.1022905,0.0008270394,0.0007092171,0.001078743,0.003311058,0.01576881,0.008592916,0.003298639,0.02206652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00114664,"about_ca_system_score_gemma":0.003776822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004679242,"about_ca_topic_score_gemma":0.001061142,"domain_scores_codex":[0.9815352,0.01426928,0.0005963028,0.001322431,0.001312722,0.000964142],"domain_scores_gemma":[0.7861617,0.1598208,0.009130803,0.02546872,0.006042945,0.01337507],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.009341114,0.006559281,0.0259306,0.001182943,0.0001449476,0.001172255,0.0120316,0.006336073,0.02065202,0.1665663,0.1608719,0.589211],"study_design_scores_gemma":[0.003004801,0.004062848,0.01402667,0.0008089209,0.0002332771,0.0004555869,0.02728004,0.02613166,0.01859576,0.4467954,0.4582391,0.0003659811],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.3510585,0.001188321,0.2435805,0.06527367,0.003008473,0.002111549,0.002596559,0.01173895,0.3194435],"genre_scores_gemma":[0.855387,0.0003329667,0.1125809,0.002806759,0.0006768194,0.002587834,0.0008332161,0.001036496,0.023758],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.974023,"threshold_uncertainty_score":0.3838226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2164827582885685,"score_gpt":0.5387398677560774,"score_spread":0.322257109467509,"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."}}