{"id":"W2139761780","doi":"10.1016/j.jsb.2007.09.012","title":"Towards automated screening of two-dimensional crystals","year":2007,"lang":"en","type":"article","venue":"Journal of Structural Biology","topic":"Enzyme Structure and Function","field":"Materials Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"National Center for Research Resources; National Institutes of Health","keywords":"Automation; Protein crystallization; Process (computing); Computer science; Crystallization; Key (lock); Materials science; Nanotechnology; Process engineering; Chemistry; Engineering; Mechanical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0007470222,0.0001182959,0.0003337732,0.0001632041,0.00006280791,0.00001035339,0.0001845388,0.0001132799,0.0005545557],"category_scores_gemma":[0.0001151798,0.00007629895,0.000107613,0.0001354647,0.000159666,0.0001542639,0.00004848751,0.0001592832,0.000003103559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002817733,"about_ca_system_score_gemma":0.00005634486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000512982,"about_ca_topic_score_gemma":0.000009345587,"domain_scores_codex":[0.9987078,0.00007042881,0.0006693327,0.000118005,0.0001943418,0.0002400478],"domain_scores_gemma":[0.998725,0.0001002683,0.0006713301,0.00009715625,0.0003223542,0.00008388251],"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":[0.0002151405,0.000002998153,0.002408739,0.000007093404,0.00002232066,0.00001432287,0.00005847584,0.000434592,0.992305,0.0007565743,0.0002379659,0.003536806],"study_design_scores_gemma":[0.001125927,0.0006295316,0.08521787,0.00003647205,0.00004058999,0.00112889,0.00006567813,0.0002991462,0.9044654,0.006559592,0.000280496,0.0001504473],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962387,0.0002765385,0.001501549,0.00008609878,0.001523997,0.00003953347,0.00001458483,0.00003227447,0.000286721],"genre_scores_gemma":[0.9756501,0.000001591912,0.02380184,0.0001054188,0.0004178741,1.015023e-7,0.000004636814,0.000006217023,0.00001224207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08783961,"threshold_uncertainty_score":0.6071996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01654945536458803,"score_gpt":0.3050343213837826,"score_spread":0.2884848660191945,"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."}}