{"id":"W3134388414","doi":"10.1039/d0ce01712d","title":"Crystallographic tomography and molecular modelling of structured organic polycrystalline powders","year":2021,"lang":"en","type":"article","venue":"CrystEngComm","topic":"Crystallography and molecular interactions","field":"Chemistry","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Drug Research and Development","funders":"Engineering and Physical Sciences Research Council; Henry Royce Institute; Pfizer","keywords":"Crystallite; Materials science; Crystallography; Tomography; Computed tomography; Crystal (programming language); Chemistry; Metallurgy; Computer science; Medicine; Radiology","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":[0.0002321311,0.0003086875,0.0002945539,0.0003314489,0.0003028674,0.0008684919,0.0007725452,0.0007331528,0.002946666],"category_scores_gemma":[0.0005578683,0.0003436959,0.0002535064,0.0007658924,0.0005015742,0.0006972794,0.000352529,0.0009390975,0.0003273599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006362846,"about_ca_system_score_gemma":0.0006886054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002253378,"about_ca_topic_score_gemma":0.002282489,"domain_scores_codex":[0.9997899,0.00001692457,0.00001109487,0.00003823253,0.0001143245,0.00002956418],"domain_scores_gemma":[0.9996566,0.0001487411,0.00005425292,0.00007320508,0.00004883295,0.00001846806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004189092,0.000157964,0.002507013,0.0003806661,0.00004222223,0.001045904,0.0002816192,0.09880735,0.867399,0.01265268,0.001409453,0.01489728],"study_design_scores_gemma":[0.0001181919,0.0002085556,0.004279146,0.00002554193,0.00002800851,0.0004553494,0.0002339509,0.5592232,0.4297574,0.001103967,0.004528839,0.00003783939],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8882918,0.0005808193,0.09884341,0.0006383242,0.00006833084,0.0001086278,0.002347856,0.0007003659,0.008420425],"genre_scores_gemma":[0.9327517,0.00059517,0.06312176,0.00003501242,0.00001190541,0.00009535596,0.001505947,0.0001412792,0.001741871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002946666,"threshold_uncertainty_score":0.009857595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01075893234327732,"score_gpt":0.2098895148921358,"score_spread":0.1991305825488585,"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."}}