{"id":"W3159748577","doi":"10.1002/9781119542650.ch6","title":"Extraction Technologies for Proteins and Peptides","year":2021,"lang":"en","type":"other","venue":"","topic":"Algal biology and biofuel production","field":"Energy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Hydrolysate; Extraction (chemistry); Biochemical engineering; Emerging technologies; Biotechnology; Protein purification; Proteome; Computational biology; Computer science; Chemistry; Biology; Biochemistry; Engineering; Chromatography; Artificial intelligence","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":[0.0004844259,0.001272035,0.0005319574,0.001338564,0.0008592395,0.0009877256,0.0005194697,0.0007504967,0.01110841],"category_scores_gemma":[0.0004200842,0.0003907342,0.0006428252,0.001436535,0.0003866387,0.001697819,0.00110977,0.001561259,0.01660222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004940677,"about_ca_system_score_gemma":0.0005740884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006135221,"about_ca_topic_score_gemma":0.001260552,"domain_scores_codex":[0.9993773,0.00004848141,0.00004289962,0.0001412596,0.0003392939,0.00005080377],"domain_scores_gemma":[0.9998417,0.00003153909,0.00002985589,0.00001992176,0.00006666416,0.00001045552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007672369,0.00008177801,0.0003647445,0.003354392,0.00004388489,0.000579564,0.0002849033,0.0004657174,0.7149369,0.01092839,0.02526003,0.243623],"study_design_scores_gemma":[0.000009894603,0.00007792407,0.0007030893,0.0002812903,0.0000302606,0.0008567976,0.0001095497,0.0008040759,0.4368303,0.003186557,0.5570683,0.00004194042],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.04316787,0.1384651,0.5638091,0.003935516,0.003478328,0.001288807,0.005975886,0.005110101,0.2347694],"genre_scores_gemma":[0.120679,0.2132125,0.3965982,0.004520707,0.0008913018,0.001539889,0.01136035,0.00187877,0.2493193],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01110841,"threshold_uncertainty_score":0.03716129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0187683166024139,"score_gpt":0.2626172772551685,"score_spread":0.2438489606527546,"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."}}