{"id":"W3188150438","doi":"10.1126/sciadv.abg6501","title":"Cellular costs underpin micronutrient limitation in phytoplankton","year":2021,"lang":"en","type":"article","venue":"Science Advances","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"H2020 European Research Council; Natural Sciences and Engineering Research Council of Canada; Dalhousie University; Simons Foundation; Compute Canada; Gordon and Betty Moore Foundation; National Science Foundation","keywords":"Micronutrient; Metaproteomics; Phytoplankton; Computer science; Biology; Nutrient; Ecology; Chemistry; Proteomics; Biochemistry","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":[0.0003352048,0.00007020413,0.00009177348,0.00004130838,0.0002473155,0.00001806186,0.0003098838,0.00003494855,0.0008491885],"category_scores_gemma":[0.00008704721,0.00006954374,0.00001791858,0.0007512705,0.0007606518,0.0004806526,0.0002113463,0.0001349243,0.000383339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002087814,"about_ca_system_score_gemma":0.00005379449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004752896,"about_ca_topic_score_gemma":0.002703693,"domain_scores_codex":[0.9991044,0.00009674895,0.0001212156,0.0002800191,0.0001216629,0.0002759764],"domain_scores_gemma":[0.9996021,0.00008058792,0.00004424903,0.0002131775,0.00001293428,0.00004697706],"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":[0.000007572517,0.00008049029,0.01711663,0.000002990943,5.255374e-7,0.00001043179,0.0003225369,0.0009925768,0.9740435,0.0003336978,0.0002394758,0.006849502],"study_design_scores_gemma":[0.0003844673,0.00008866321,0.1016028,0.0000282357,0.000002940931,0.000012778,0.000964079,0.0001255151,0.8343385,0.009583083,0.05262756,0.0002413437],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899359,0.0004563176,0.0001513385,0.0003471159,0.0002037836,0.0000725284,0.00000204253,0.0000121465,0.008818867],"genre_scores_gemma":[0.998138,0.00009160201,0.001003269,0.0004712043,0.00001042079,0.00000518957,0.00001505839,0.000002513325,0.0002627984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.139705,"threshold_uncertainty_score":0.9298019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009770020414851437,"score_gpt":0.2486799783891883,"score_spread":0.2389099579743369,"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."}}