{"id":"W2143437919","doi":"10.5376/cmb.2014.04.0013","title":"In-silico analysis predicting the best model for photosystemIID2 Protein of Spinaciaolearacea using multiple templates","year":2014,"lang":"en","type":"article","venue":"Computational Molecular Biology","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"In silico; UniProt; Template; Spinach; Computational biology; Protein structure prediction; Computer science; Chemistry; Bioinformatics; Protein structure; Biology; Biochemistry; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003679839,0.0001391571,0.0002961686,0.000147062,0.00008842113,0.000008492262,0.0001764429,0.0001095267,0.000001177802],"category_scores_gemma":[0.0003217202,0.0001118657,0.0001738196,0.0002580144,0.0001036737,0.000002698678,0.0001059163,0.00006005,4.381705e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001252226,"about_ca_system_score_gemma":0.00004851393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004353663,"about_ca_topic_score_gemma":0.00003708112,"domain_scores_codex":[0.9989479,0.0001125704,0.0003372047,0.0003254215,0.00007470549,0.0002022173],"domain_scores_gemma":[0.9993411,0.00007195137,0.0001947652,0.0001999031,0.0001652343,0.00002700134],"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":[0.00005080756,0.00004357532,0.01028532,0.00002735422,0.0003129403,2.092596e-7,0.00002897843,0.2671242,0.7149132,0.007096838,0.00000402843,0.0001124981],"study_design_scores_gemma":[0.0005824862,0.0001948527,0.0005727779,0.00001107057,0.0001241073,0.000003131056,0.00005216158,0.9467984,0.04068791,0.0106904,0.000142486,0.0001402635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5330811,0.000280322,0.4662576,0.00005489758,0.00002543111,0.0002477212,0.00002958995,0.000002186908,0.00002109214],"genre_scores_gemma":[0.9762139,0.000005250919,0.02340576,0.00009896467,0.00005152066,0.00006843641,0.0001197837,0.00001317778,0.00002320785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6796741,"threshold_uncertainty_score":0.4561751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0187321794491058,"score_gpt":0.3004691566742135,"score_spread":0.2817369772251077,"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."}}