{"id":"W4213239631","doi":"10.1016/j.aquatox.2022.106123","title":"Nano-sized polystyrene plastics toxicity to microalgae Chlorella vulgaris: Toxicity mitigation using humic acid","year":2022,"lang":"en","type":"article","venue":"Aquatic Toxicology","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Alzahra University; Al Zahra University; Iran National Science Foundation","keywords":"Chlorella vulgaris; Toxicity; Chemistry; Polystyrene; Humic acid; Algae; Acute toxicity; Sorption; Photosynthesis; Chlorophyll; Zeta potential; Chlorophyll a; Nuclear chemistry; Environmental chemistry; Food science; Botany; Biology; Nanoparticle; Biochemistry; Organic chemistry; Materials science; Adsorption; Nanotechnology; Polymer","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005656531,0.0003147445,0.0003999863,0.0001528201,0.0007597838,0.0000417746,0.0004579364,0.0001645791,0.006285404],"category_scores_gemma":[0.0004204271,0.0003441373,0.0001003499,0.0006058664,0.0002060934,0.00009001973,0.0007275917,0.0003561226,0.000662327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001038102,"about_ca_system_score_gemma":0.0001173336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004503977,"about_ca_topic_score_gemma":0.0007898937,"domain_scores_codex":[0.9971891,0.0003357614,0.0005867607,0.0006521171,0.0004980377,0.0007382336],"domain_scores_gemma":[0.9987164,0.0003531988,0.000258832,0.0003754379,0.0000109786,0.0002851387],"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":[0.0001293529,0.0002400677,0.002619538,0.00000730149,0.00002777766,0.0000176772,0.0005154575,0.01723464,0.9758511,0.0002096196,0.002139981,0.001007525],"study_design_scores_gemma":[0.002743248,0.002086222,0.01668194,0.0000326002,0.0002671285,0.0003882961,0.0004964811,0.1397841,0.8219179,0.002648621,0.01152269,0.00143075],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9547787,0.00004125217,0.0423329,0.0004227826,0.001090348,0.0005168678,0.0001222266,0.00006621776,0.0006286919],"genre_scores_gemma":[0.9913964,0.000004974972,0.006416086,0.001573294,0.00009927247,0.00005761863,0.00004192306,0.00003613771,0.0003743182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1539332,"threshold_uncertainty_score":0.9999011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01326376457447266,"score_gpt":0.2329276277042626,"score_spread":0.21966386312979,"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."}}