{"id":"W1987985795","doi":"10.1002/bmb.2006.49403401058","title":"Present at the flood: How structural molecular biology came about: Dickerson, Richard E.","year":2006,"lang":"en","type":"article","venue":"Biochemistry and Molecular Biology Education","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":"Reading (process); Period (music); Plan (archaeology); Classics; Sociology; Philosophy; Art history; History; Library science; Computer science; Archaeology; Linguistics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000279934,0.0003563183,0.0002375097,0.00006229506,0.0002808726,0.00007174192,0.0004387801,0.0005774953,0.00003697395],"category_scores_gemma":[0.0002200036,0.0002676352,0.0001522135,0.0001442552,0.0009766694,0.000005816361,0.0004073061,0.0002201659,0.0000121222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005332479,"about_ca_system_score_gemma":0.0003306681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001381805,"about_ca_topic_score_gemma":0.00001889478,"domain_scores_codex":[0.9980401,0.0001536581,0.0003422017,0.0006690966,0.0001874882,0.0006074135],"domain_scores_gemma":[0.9986756,0.00002767129,0.0001851297,0.0006782911,0.0002144826,0.0002187586],"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":[0.00004733236,0.00006145591,0.00250097,0.00006490837,0.00007773215,0.000002042346,0.00002820603,0.000002774657,0.9804465,0.0004060599,0.01038926,0.0059728],"study_design_scores_gemma":[0.0004647871,0.0002072705,0.001308001,0.00001497412,0.00004808699,0.00007314653,0.0001728047,0.00005635736,0.9004578,0.001365079,0.09546357,0.000368139],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9770182,0.01247864,0.002839639,0.005350616,0.0004355787,0.0004175088,0.0001055841,0.00002191645,0.001332267],"genre_scores_gemma":[0.9911766,0.0004727184,0.0009835107,0.0009597314,0.0006803809,0.0000986169,0.002803982,0.00002796254,0.002796519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08507431,"threshold_uncertainty_score":0.9999776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006038679957376746,"score_gpt":0.2810325004297238,"score_spread":0.2749938204723471,"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."}}