{"id":"W2952355835","doi":"10.1002/chin.200637255","title":"Design of Targeting Ligands in Medicinal Inorganic Chemistry","year":2006,"lang":"en","type":"article","venue":"ChemInform","topic":"Chemical Synthesis and Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Chemistry; Click chemistry; Combinatorial chemistry; Nanotechnology","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":[0.0004303049,0.0005077159,0.00051569,0.0002611311,0.0002608461,0.0007253668,0.0007394648,0.000506494,0.003555699],"category_scores_gemma":[0.0003061692,0.000272815,0.0002295426,0.0003073534,0.0003114283,0.0005163035,0.0005163422,0.0006045474,0.0026858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005722612,"about_ca_system_score_gemma":0.0003465903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002529532,"about_ca_topic_score_gemma":0.0003877575,"domain_scores_codex":[0.999841,0.00004137296,0.000008684377,0.00003242542,0.00003844824,0.00003801161],"domain_scores_gemma":[0.9999419,0.00001097117,0.00001306153,0.000005599157,0.0000105489,0.00001782211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007982051,0.000373437,0.0003926173,0.00106872,0.00005372896,0.0006080273,0.0001690334,0.01246034,0.7665116,0.052887,0.009756362,0.154921],"study_design_scores_gemma":[0.0004519829,0.001862893,0.0003432551,0.0001636171,0.00008684951,0.0007719382,0.00007606632,0.02917325,0.8142264,0.01362154,0.1391637,0.00005850401],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3243983,0.0420549,0.5290656,0.003729317,0.00129587,0.001775149,0.001612359,0.00364929,0.09241924],"genre_scores_gemma":[0.8219534,0.01648219,0.1286515,0.00156717,0.0001554405,0.0008708244,0.0009509882,0.0001511067,0.02921742],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003555699,"threshold_uncertainty_score":0.01189494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005071209046733474,"score_gpt":0.2021188751455419,"score_spread":0.1970476660988084,"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."}}