{"id":"W2079357492","doi":"10.1038/nchembio0507-247","title":"High-throughput screening flows along","year":2007,"lang":"en","type":"article","venue":"Nature Chemical Biology","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Institute for Nanotechnology","funders":"","keywords":"Throughput; Microfluidics; Photolithography; Nanotechnology; High-throughput screening; Computer science; Materials science; Bioinformatics; Biology; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.0001705061,0.0001611933,0.000148206,0.0000288566,0.00006461273,0.000006291365,0.000221953,0.0009176022,0.000008602003],"category_scores_gemma":[0.0001317774,0.0001412922,0.00008413462,0.0001219579,0.0001266582,0.000001961289,0.0001610308,0.0004104485,0.000006906665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001397402,"about_ca_system_score_gemma":0.00001435531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009941604,"about_ca_topic_score_gemma":0.00001277922,"domain_scores_codex":[0.9989353,0.00001315139,0.0002064263,0.0004476728,0.00005590367,0.0003415868],"domain_scores_gemma":[0.999375,0.00003193477,0.00006749997,0.0003590053,0.00007998293,0.00008660475],"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":[0.00004646544,0.00002373445,0.0002935405,0.000002293426,0.0000153097,0.000002047082,0.000001941627,0.000001106731,0.9773897,0.003262093,0.001566581,0.0173952],"study_design_scores_gemma":[0.0001867109,0.00005097463,0.0001997441,0.000004507302,0.000006366413,0.00002464742,0.000004709997,0.000006868431,0.8341138,0.00185641,0.1633829,0.0001623368],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8420925,0.0007929154,0.1552449,0.000674969,0.0001612251,0.0001678495,0.00002790483,0.0001065812,0.0007311328],"genre_scores_gemma":[0.8538491,0.00004752932,0.1436649,0.001220052,0.0006307067,0.000006417702,0.0005095869,0.00001790051,0.00005388203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1618163,"threshold_uncertainty_score":0.7077389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006576098987045398,"score_gpt":0.2966793149574817,"score_spread":0.2901032159704363,"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."}}