{"id":"W4410830697","doi":"10.1021/acs.biomac.5c00192","title":"Designing Amyloid-Like Protein Aggregates from Microalgal Biomass","year":2025,"lang":"en","type":"article","venue":"Biomacromolecules","topic":"Algal biology and biofuel production","field":"Energy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Amyloid (mycology); Chemistry; Biomass (ecology); Protein aggregation; Amyloid fibril; Biophysics; Chemical engineering; Biochemistry; Amyloid β; Biology; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015142,0.0002715287,0.0002341485,0.0001673587,0.000266699,0.00006718044,0.0003098387,0.0003069279,0.0001619423],"category_scores_gemma":[0.00008331148,0.0002362796,0.0001175279,0.0004217803,0.0002482817,0.00009524289,0.0001276611,0.0001325133,0.0003100882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006098153,"about_ca_system_score_gemma":0.00006553333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002677367,"about_ca_topic_score_gemma":0.0002055561,"domain_scores_codex":[0.9984215,0.0001729392,0.0003047606,0.0006049398,0.0001114097,0.0003844884],"domain_scores_gemma":[0.9993309,0.00004862299,0.0001128419,0.000371393,0.00007616576,0.00006005173],"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":[0.0001211607,0.00006717485,0.0007982653,0.00002618196,0.0001549813,0.00003431744,0.00004743404,7.634135e-7,0.9758413,0.00308053,0.0007254192,0.01910241],"study_design_scores_gemma":[0.000420445,0.00005733085,0.002870046,0.00009008851,0.00003924242,0.000007258436,0.00006074014,0.00001501679,0.9511434,0.008708148,0.03631387,0.0002744262],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822497,0.007425503,0.002502842,0.001406987,0.0008340314,0.0003547383,0.00004304957,0.0004175865,0.004765524],"genre_scores_gemma":[0.9906349,0.00002493918,0.006571855,0.0002996918,0.000194814,0.00005715838,0.0002138245,0.00002251781,0.001980274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03558845,"threshold_uncertainty_score":0.9635203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009852832230389926,"score_gpt":0.231386811639875,"score_spread":0.221533979409485,"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."}}