{"id":"W4309022734","doi":"10.1016/j.drudis.2022.103443","title":"Optical tweezers for drug discovery","year":2022,"lang":"en","type":"review","venue":"Drug Discovery Today","topic":"Transgenic Plants and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Drug discovery; Optical tweezers; Computational biology; Workflow; Tweezers; Drug; Computer science; Nanotechnology; Chemistry; Bioinformatics; Medicine; Materials science; Biology; Pharmacology; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000263482,0.0005202824,0.0009004991,0.00007250075,0.0002407477,0.0001786468,0.0007418011,0.000207684,0.00006322573],"category_scores_gemma":[0.00004358432,0.00043669,0.001072297,0.0001496917,0.0001112652,0.00002084498,0.0002622808,0.0003132005,0.00002338513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000607422,"about_ca_system_score_gemma":0.0004860588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001579814,"about_ca_topic_score_gemma":0.00003402226,"domain_scores_codex":[0.9977005,0.00009177847,0.0005471341,0.0009411669,0.0002277834,0.0004916962],"domain_scores_gemma":[0.9986677,0.0001580004,0.0002107816,0.0008249105,0.00001620468,0.000122443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001468493,0.0008176342,0.000009941182,0.009048101,0.001530795,0.00001986684,0.0001060367,0.00006393342,0.0007085791,0.01154531,0.2249254,0.7510775],"study_design_scores_gemma":[0.000258319,0.00003912328,0.000001784703,0.000296643,0.0005007521,0.00002096457,0.00005036176,0.000001343478,0.0002054906,0.0000774811,0.9979709,0.0005767964],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002182342,0.987657,0.002059764,0.0001418849,0.0005545361,0.001393336,0.005723868,0.00002900388,0.002222373],"genre_scores_gemma":[0.000394866,0.9635162,0.0002026198,0.0001707808,0.000608833,0.001427618,0.01098635,0.0001160136,0.02257673],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7730455,"threshold_uncertainty_score":0.9998085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0273417655993808,"score_gpt":0.3077747055619722,"score_spread":0.2804329399625914,"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."}}