{"id":"W2611021352","doi":"10.1073/pnas.1614680114","title":"Retrospective analysis of natural products provides insights for future discovery trends","year":2017,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":544,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Center for Complementary and Integrative Health; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Natural (archaeology); Novelty; Natural product; Chemical space; Relevance (law); Space (punctuation); Function (biology); Data science; Biochemical engineering; Computer science; Drug discovery; Biology; Engineering; Evolutionary biology; Bioinformatics; Psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01056845,0.0005333549,0.0009117368,0.007028988,0.0005796344,0.002966142,0.0006264753,0.0004901656,0.001986502],"category_scores_gemma":[0.02525384,0.0002933991,0.001105466,0.008211922,0.0007623,0.002435154,0.00096866,0.0009666534,0.000988489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007582422,"about_ca_system_score_gemma":0.0008026042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002429077,"about_ca_topic_score_gemma":0.003372794,"domain_scores_codex":[0.9947376,0.001125213,0.0008806731,0.00157252,0.001423291,0.0002607091],"domain_scores_gemma":[0.9497355,0.02835925,0.009597729,0.006486902,0.005122209,0.0006984051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004554079,0.00008349297,0.8855513,0.0007667158,0.0007541045,0.0003095848,0.0003357194,0.004151257,0.005406899,0.004178478,0.003077595,0.09492943],"study_design_scores_gemma":[0.0000250673,0.0004484437,0.9007132,0.0002647812,0.0007019073,0.001252611,0.001016728,0.01979056,0.005923453,0.01174837,0.05801757,0.0000973526],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8582289,0.02075317,0.05049072,0.001795312,0.0002731438,0.0002732514,0.05585348,0.0004758323,0.01185617],"genre_scores_gemma":[0.9349578,0.003687425,0.01910195,0.0002337821,0.0001680385,0.0001659538,0.03999346,0.0000852395,0.001606285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01056845,"threshold_uncertainty_score":0.05589199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03077124441528254,"score_gpt":0.3114949130683621,"score_spread":0.2807236686530796,"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."}}