{"id":"W1607491091","doi":"10.1002/9780470661345.smc182","title":"Supramolecular Approaches to Medicinal Chemistry","year":2012,"lang":"en","type":"other","venue":"Supramolecular chemistry","topic":"Chemical Synthesis and Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Supramolecular chemistry; Molecular recognition; Template; Chemistry; Nanotechnology; Combinatorial chemistry; Computational biology; Materials science; Molecule; Organic chemistry; Biology","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","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002759008,0.001051311,0.0008848922,0.00007419091,0.00008619447,0.00007985663,0.001060236,0.001596714,0.008187195],"category_scores_gemma":[0.0002759027,0.001078769,0.0007472525,0.0003501704,0.0002471073,0.000003615965,0.0006064263,0.0005332929,0.0003245855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007323628,"about_ca_system_score_gemma":0.0001786667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006091833,"about_ca_topic_score_gemma":0.000006593124,"domain_scores_codex":[0.9959694,0.00006795477,0.00055473,0.001554706,0.0007302006,0.001122997],"domain_scores_gemma":[0.9967917,0.00001492819,0.0003125872,0.001881521,0.00005758063,0.0009417133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003407597,0.0001919633,0.00008103576,0.0004171034,0.0005829584,0.00003499686,0.00001034519,0.000005717884,0.7824674,0.000009198521,0.2146765,0.001488627],"study_design_scores_gemma":[0.000240188,0.00001565529,0.000002671212,0.0001065353,0.0002216547,0.0000401717,0.00002707905,0.000004743395,0.4750434,0.000008586707,0.5235714,0.000717922],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007500059,0.01650898,0.004105324,0.0006941634,0.0002167333,0.0006253642,0.000335104,0.0002790032,0.9697353],"genre_scores_gemma":[0.09303904,0.0004723508,0.003777327,0.0009512719,0.00582837,0.0003322512,0.005145594,0.002251567,0.8882023],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3088949,"threshold_uncertainty_score":0.9996994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02361153969440122,"score_gpt":0.2152981447577349,"score_spread":0.1916866050633337,"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."}}