{"id":"W1976081621","doi":"10.1371/journal.pntd.0001412","title":"Integrated Dataset of Screening Hits against Multiple Neglected Disease Pathogens","year":2011,"lang":"en","type":"article","venue":"PLoS neglected tropical diseases","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Prioritization; Drug discovery; Neglected tropical diseases; Computational biology; Pathogen; Disease; Biology; Drug; Bioinformatics; Medicine; Pharmacology; Immunology; Management science; Engineering","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":[0.00116327,0.001346936,0.002208601,0.004362049,0.0008000824,0.00158217,0.002065304,0.002084395,0.005946067],"category_scores_gemma":[0.003878186,0.0004600546,0.001394485,0.006961326,0.0003681449,0.0007500637,0.001253829,0.001172438,0.002629961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009707364,"about_ca_system_score_gemma":0.002505189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008057394,"about_ca_topic_score_gemma":0.01751918,"domain_scores_codex":[0.9983797,0.0002277142,0.0002038167,0.0003395351,0.0006682892,0.0001808794],"domain_scores_gemma":[0.9972538,0.0009761587,0.0003174511,0.0003889789,0.0006678093,0.0003958855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.008377335,0.004228833,0.1385347,0.01789112,0.004204679,0.005397905,0.0003342546,0.1074733,0.1038165,0.006511321,0.4133494,0.1898808],"study_design_scores_gemma":[0.002841675,0.003446745,0.2755572,0.0007951177,0.003015885,0.005884082,0.0008204278,0.132716,0.07978743,0.006652803,0.4880172,0.0004654701],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1375945,0.004736951,0.00453456,0.0004666216,0.0001412529,0.0004429376,0.8438169,0.001612767,0.0066536],"genre_scores_gemma":[0.06111773,0.0008755889,0.00611002,0.000151443,0.00002769405,0.0002026396,0.9305911,0.00003575846,0.0008880667],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008057394,"threshold_uncertainty_score":0.01989156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0520694856254129,"score_gpt":0.2587404904442505,"score_spread":0.2066710048188375,"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."}}