{"id":"W4389478361","doi":"10.1021/acsnano.3c08077","title":"Cell-Targeted Metal-Phenolic Nanoalgaecide in Hydroponic Cultivation to Enhance Food Sustainability","year":2023,"lang":"en","type":"article","venue":"ACS Nano","topic":"Algal biology and biofuel production","field":"Energy","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"State Key Laboratory of Polymer Materials Engineering; National Key Research and Development Program of China; Chinese Academy of Agricultural Sciences; Sichuan University; Department of Science and Technology of Sichuan Province; National Natural Science Foundation of China","keywords":"Hydroponics; Sustainability; Photobioreactor; Population; Chlorella vulgaris; Environmental science; Biotechnology; Photosynthesis; Agriculture; Algal bloom; Biosafety; Nutrient; Biology; Algae; Agronomy; Ecology; Botany; Biofuel","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":[0.00007961605,0.000282298,0.0001964987,0.0001218171,0.00009846275,0.0002492451,0.0002172859,0.0002549583,0.0005262543],"category_scores_gemma":[0.00007715081,0.0001224064,0.000228213,0.000129436,0.0001495487,0.0002241491,0.0002235144,0.0004218977,0.0001737763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003250433,"about_ca_system_score_gemma":0.0002238189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001411026,"about_ca_topic_score_gemma":0.002887684,"domain_scores_codex":[0.99994,0.000004550867,0.000004301104,0.00001941476,0.00002083953,0.00001085848],"domain_scores_gemma":[0.9999493,0.000005864822,0.00001342564,0.000004650583,0.00001345308,0.00001326347],"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":[0.00001061143,0.000009091808,0.00003471467,0.0000253946,0.000001352195,0.00001703716,0.000003976962,0.00009681656,0.9988986,0.00003283147,0.00002453145,0.0008449843],"study_design_scores_gemma":[0.00000548465,0.0001035698,0.0005538396,0.000003866699,0.000008018421,0.00002533101,0.00001371987,0.001588865,0.9960629,0.00001820973,0.001611714,0.000004398948],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864586,0.001049134,0.009214423,0.0001247624,0.00006577054,0.00007377256,0.0003060203,0.0002445302,0.00246307],"genre_scores_gemma":[0.9862509,0.0007807706,0.01001673,0.00005677118,0.00000726881,0.00005528672,0.0002259676,0.00002774448,0.002578546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001411026,"threshold_uncertainty_score":0.002805591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01022180637342785,"score_gpt":0.2644063325783969,"score_spread":0.254184526204969,"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."}}