{"id":"W2018764113","doi":"10.1529/biophysj.106.093435","title":"Structural Modeling of Snow Flea Antifreeze Protein","year":2006,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Physiological and biochemical adaptations","field":"Environmental Science","cited_by":65,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Canadian Institutes of Health Research","keywords":"Polyproline helix; Antiparallel (mathematics); Antifreeze protein; Chemistry; Intramolecular force; Crystallography; Hydrogen bond; Circular dichroism; Intermolecular force; Protein secondary structure; Antifreeze; Stereochemistry; Protein structure; Helix (gastropod); Peptide; Molecule; Biochemistry; Biology; Organic chemistry; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000136976,0.0005430174,0.0004936363,0.0001838017,0.0008409362,0.0005241242,0.0007980943,0.0007470068,0.003222211],"category_scores_gemma":[0.0001887334,0.0002251811,0.0003776813,0.0002615325,0.0002803216,0.0004668214,0.0002373647,0.0006525562,0.0003723467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008861781,"about_ca_system_score_gemma":0.0009413639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01559641,"about_ca_topic_score_gemma":0.01358538,"domain_scores_codex":[0.9999472,0.000009220817,0.00000166034,0.00001202281,0.00001509916,0.00001476805],"domain_scores_gemma":[0.9999384,0.00001389651,0.00001000061,0.00000529922,0.00001349564,0.00001897067],"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":[0.001677294,0.0005593307,0.0118868,0.0006009356,0.0002920618,0.003018384,0.0009902105,0.6972469,0.2367261,0.02226901,0.007777961,0.01695508],"study_design_scores_gemma":[0.0001399826,0.0001808361,0.005782346,0.00002858142,0.00004954915,0.0001695459,0.0003566326,0.9749279,0.01062516,0.002827917,0.004879727,0.00003181742],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843307,0.000506383,0.008276785,0.0004803307,0.00003741781,0.0000288755,0.001013343,0.0003597645,0.0049663],"genre_scores_gemma":[0.9920377,0.0004738043,0.003898211,0.00008018823,0.000009454003,0.00003256805,0.00165819,0.00009594785,0.001713921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01559641,"threshold_uncertainty_score":0.03101128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01791262225017273,"score_gpt":0.2196209270405182,"score_spread":0.2017083047903454,"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."}}