{"id":"W4405739510","doi":"10.1021/acsomega.4c08735","title":"Human-Validated Neural Networks for Precise Amastigote Categorization and Quantification to Accelerate Drug Discovery in Leishmaniasis","year":2024,"lang":"en","type":"article","venue":"ACS Omega","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"IONICS Mass Spectrometry (Canada)","funders":"Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Universidade Federal de Mato Grosso do Sul; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Amastigote; Leishmania; Computational biology; Leishmaniasis; Categorization; Drug; Drug discovery; Artificial intelligence; Machine learning; Computer science; Biology; Medicine; Pharmacology; Bioinformatics; Pathology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001412996,0.0006015478,0.0004075949,0.0003624204,0.0001516048,0.0005346526,0.0005180471,0.0005549941,0.001343342],"category_scores_gemma":[0.002939286,0.0002326334,0.0003386418,0.000225194,0.0003229244,0.0004401558,0.0004707714,0.0007376327,0.0002924886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008011857,"about_ca_system_score_gemma":0.0008903086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006717801,"about_ca_topic_score_gemma":0.008866774,"domain_scores_codex":[0.9996907,0.000132989,0.00001238258,0.00006495773,0.00006205201,0.00003690356],"domain_scores_gemma":[0.9994134,0.000286919,0.00006562354,0.00005282261,0.000158167,0.00002306984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004441688,0.0002247287,0.006409354,0.0001656878,0.0001293883,0.00008296483,0.00003930966,0.8171833,0.02368511,0.002031077,0.002651058,0.1469539],"study_design_scores_gemma":[0.000006226117,0.00005386382,0.0004415787,0.000006478943,0.000007701937,0.000008766745,0.000004037472,0.9950339,0.003646386,0.0004785465,0.0003093613,0.000003280852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5301663,0.003199677,0.4539362,0.001187385,0.0001673121,0.000163473,0.0008274755,0.003342706,0.007009375],"genre_scores_gemma":[0.9481314,0.0004826271,0.0481555,0.0002372735,0.00002074525,0.00008316125,0.0005515387,0.00004891973,0.002288745],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006717801,"threshold_uncertainty_score":0.0133574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03703167476261961,"score_gpt":0.3274795200670495,"score_spread":0.2904478453044299,"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."}}