{"id":"W7095846136","doi":"","title":"Reprint requests:","year":2008,"lang":"en","type":"article","venue":"","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reprint; Emerging technologies; Ridiculous; Quarter (Canadian coin)","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":[0.0001909889,0.00008576092,0.00007968767,0.00003213172,0.00007813601,0.00001010027,0.0002038234,0.0001153069,0.000146972],"category_scores_gemma":[0.0002320057,0.00006734688,0.00006164191,0.00005794872,0.0001999815,0.000001561156,0.0001709667,0.00007523489,0.0002344929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008511684,"about_ca_system_score_gemma":0.00009371291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002271641,"about_ca_topic_score_gemma":0.00001294247,"domain_scores_codex":[0.9991186,0.00001974459,0.0001956359,0.0001929607,0.0002229464,0.0002501568],"domain_scores_gemma":[0.9993311,0.000006292246,0.00002768019,0.0003807948,0.00009192589,0.0001622723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001517897,0.0003140006,0.01839454,0.00007587867,0.0001165449,0.00005791212,0.0002954911,0.00001271274,0.7133337,0.001097141,0.2254484,0.04070185],"study_design_scores_gemma":[0.0005431768,0.0004706122,0.01203704,0.000007053193,0.000003594701,0.0001296031,0.0001184183,0.0001630106,0.4304724,0.0002672334,0.555523,0.000264831],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8703787,0.0002482188,0.007087925,0.0007841582,0.0001847247,0.0001829632,0.000005738724,0.00003585364,0.1210917],"genre_scores_gemma":[0.9772925,0.001498314,0.005714027,0.0007405438,0.0002484122,0.000008405074,0.00005071531,0.000009890436,0.01443719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3300746,"threshold_uncertainty_score":0.3014009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02623175871998288,"score_gpt":0.2924371044797269,"score_spread":0.266205345759744,"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."}}