{"id":"W3214434543","doi":"10.26434/chemrxiv.12546389.v1","title":"Minimizing Polymorphic Risk Through Cooperative Computational and Experimental Exploration","year":2020,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Crystallography and molecular interactions","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Durham University; Newcastle University; University of Southampton; Engineering and Physical Sciences Research Council; York University","keywords":"Iproniazid; Polymorphism (computer science); Crystal structure prediction; Crystallization; Computer science; Crystal structure; Chemistry; Crystallography; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00608202,0.001898227,0.002180233,0.001720962,0.001130736,0.0020738,0.00359904,0.002203946,0.002709756],"category_scores_gemma":[0.01486876,0.001070399,0.001682385,0.001337902,0.002942163,0.003202658,0.004215538,0.0023981,0.0005087464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001274221,"about_ca_system_score_gemma":0.003421839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002219273,"about_ca_topic_score_gemma":0.003310874,"domain_scores_codex":[0.9982297,0.0009474171,0.00006279589,0.0002201915,0.0003922642,0.0001476243],"domain_scores_gemma":[0.9900858,0.007159641,0.0005143911,0.001567919,0.0004291296,0.0002431038],"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":[0.0001331292,0.0001578042,0.002044817,0.0001908041,0.0001058517,0.0001464287,0.0001022512,0.9469416,0.001767639,0.02579465,0.0006489339,0.02196616],"study_design_scores_gemma":[0.00004703763,0.00007866848,0.0001400722,0.00001325299,0.00002390458,0.0000245334,0.00003531069,0.9545961,0.0006395525,0.04367204,0.0007172342,0.00001224956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.215624,0.001731656,0.7602977,0.003109137,0.00009518033,0.0003724737,0.0004369856,0.001945099,0.01638779],"genre_scores_gemma":[0.7161709,0.0007766861,0.2794041,0.0004529167,0.00008476689,0.0007839652,0.0006837611,0.000348804,0.001294136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00608202,"threshold_uncertainty_score":0.03216517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04201253433678692,"score_gpt":0.292408763205288,"score_spread":0.250396228868501,"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."}}