{"id":"W7004727556","doi":"","title":"Teaching Evidence","year":2006,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dozen; Government (linguistics); State (computer science); Federal state; Slovak; Federal Rules of Evidence; Section (typography)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003192684,0.0001418565,0.0001292089,0.00003051121,0.0001275866,0.00006992213,0.000278617,0.0001106557,0.00009021126],"category_scores_gemma":[0.0001199313,0.0001404663,0.000128813,0.00006337793,0.00006829704,0.00001319358,0.0001379253,0.0001711424,0.0001059936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002070047,"about_ca_system_score_gemma":0.00002776647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00302791,"about_ca_topic_score_gemma":0.001176327,"domain_scores_codex":[0.9989619,0.00008337678,0.0002036715,0.0003717574,0.0001477381,0.0002315135],"domain_scores_gemma":[0.9992117,0.00001567727,0.00006792064,0.0005773226,0.00005649811,0.00007083736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001228953,0.00004505855,0.00317807,0.00001026557,0.0000198543,0.000009390011,0.000003654631,0.00001343097,0.9561673,0.002196462,0.03729536,0.001048831],"study_design_scores_gemma":[0.0001190582,0.00007246014,0.000887756,0.00003211645,0.00002923147,0.00001157267,0.000008796267,0.00002795396,0.6356672,0.0008156021,0.3621012,0.000227038],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8818433,0.004420498,0.007736429,0.0004711234,0.00005454819,0.0002425035,0.000003367387,0.0001862338,0.105042],"genre_scores_gemma":[0.9831321,0.00006582525,0.004385499,0.0009012406,0.0005296228,0.00002071915,0.00004800829,0.00002386304,0.01089312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3248059,"threshold_uncertainty_score":0.572805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009521591848168663,"score_gpt":0.2677031372460062,"score_spread":0.2581815453978376,"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."}}