{"id":"W4392302913","doi":"10.1016/j.biortech.2024.130508","title":"Protein extraction from chlorella pyrenoidosa microalgae: Green methodologies, functional assessment, and waste stream valorization for bioenergy production","year":2024,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Algal biology and biofuel production","field":"Energy","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Minjiang University; Natural Science Foundation of Fujian Province","keywords":"Chlorella pyrenoidosa; Bioenergy; Extraction (chemistry); Biofuel; Biomass (ecology); Environmental science; Waste management; Biorefinery; Production (economics); Pulp and paper industry; Biochemical engineering; Chemistry; Chlorella; Engineering; Algae; Biology; Botany; Ecology","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":[0.0003699552,0.0005193875,0.0002377529,0.0003334539,0.0003979768,0.0004084944,0.0001982539,0.0002871444,0.0003308207],"category_scores_gemma":[0.0002088592,0.0002029425,0.0002686572,0.0003215457,0.0002024378,0.0003732864,0.0003420362,0.0005088503,0.0001945228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002851243,"about_ca_system_score_gemma":0.0004507174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002143002,"about_ca_topic_score_gemma":0.004817789,"domain_scores_codex":[0.9998054,0.00002591214,0.00001674626,0.00004903633,0.00006894804,0.00003398611],"domain_scores_gemma":[0.9999201,0.00001368436,0.00001582906,0.000007216064,0.00002696604,0.0000161726],"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":[0.00003348325,0.000006589269,0.0002148671,0.00003934349,0.000003839772,0.00001359663,0.00001720784,0.0000322039,0.9984439,0.00001457586,0.000009017791,0.001171413],"study_design_scores_gemma":[0.000002766581,0.00004149965,0.004822861,0.000005744348,0.00001169402,0.00006503711,0.00004117214,0.0003211923,0.9935104,0.00003174399,0.001141692,0.000004100937],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808452,0.002524656,0.0148508,0.0001411411,0.0000265171,0.00004491175,0.0004729391,0.00004073144,0.001053135],"genre_scores_gemma":[0.9733486,0.003045055,0.01680501,0.00008486879,0.00001125973,0.00003959689,0.001429773,0.00003813461,0.005197636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002143002,"threshold_uncertainty_score":0.004261076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.038400251356912,"score_gpt":0.2993843235725898,"score_spread":0.2609840722156778,"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."}}