{"id":"W4411166513","doi":"10.31542/27qd3a63","title":"Teaching, Technology, and Time: Revisiting Ellen Rose’s Call for Reflection in an AI Era","year":2025,"lang":"en","type":"article","venue":"Pedagogical Inquiry and Practice","topic":"Legal Education and Practice Innovations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Rose (mathematics); Deep time; Reflection (computer programming); History; Computer science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003485374,0.00008248,0.000120951,0.000238164,0.0009166744,0.0003098117,0.00009221242,0.0002005831,0.00006519922],"category_scores_gemma":[0.01335139,0.00008046826,0.00001427,0.000590892,0.0002448763,0.001949841,0.00003938056,0.0007599639,0.000007147457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000521221,"about_ca_system_score_gemma":0.0002651391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008782396,"about_ca_topic_score_gemma":0.0002050121,"domain_scores_codex":[0.9985353,0.0006716485,0.0002294547,0.000271444,0.0001016,0.0001905425],"domain_scores_gemma":[0.9971787,0.002337985,0.0001214803,0.0001078975,0.0001917368,0.00006219257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001994995,0.0002531272,0.001423927,0.00004190841,0.00001546454,0.000002411537,0.03313072,0.000002251531,0.0005814094,0.8663785,0.004103168,0.09386759],"study_design_scores_gemma":[0.0002239404,0.00007782471,0.0005772786,0.00002856873,0.00003057925,0.000007701341,0.02503718,0.0001430273,0.00001292396,0.01406194,0.9596941,0.0001049233],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09881336,0.0008482006,0.00287883,0.7250877,0.0004663134,0.000650961,0.000003997639,0.0001737745,0.1710768],"genre_scores_gemma":[0.9542069,0.0005358653,0.009515707,0.0143826,0.0008534881,0.0001124723,0.00001776809,0.00001108827,0.02036415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.955591,"threshold_uncertainty_score":0.9949596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2513450595105244,"score_gpt":0.5580567274845407,"score_spread":0.3067116679740163,"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."}}