{"id":"W6911520655","doi":"10.5281/zenodo.11010726","title":"Code for article \"Trophic controls on thermal adaptation of phytoplankton size and stoichiometry\"","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Code (set theory); Adaptation (eye); Phytoplankton; Ectotherm; Thermal","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006702346,0.001590979,0.001135737,0.001839371,0.0007778647,0.001760036,0.003424769,0.001840585,0.7486444],"category_scores_gemma":[0.002335637,0.0007940956,0.00150956,0.001832316,0.0004794535,0.001335182,0.002238072,0.001139669,0.506817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001777029,"about_ca_system_score_gemma":0.001337172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009233274,"about_ca_topic_score_gemma":0.01020205,"domain_scores_codex":[0.999463,0.00005087639,0.00003831031,0.00009802511,0.0002575018,0.0000922683],"domain_scores_gemma":[0.9990953,0.0001643567,0.00004047877,0.0001999362,0.0003633451,0.0001365876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008513597,0.00003513236,0.0002405011,0.0003794002,0.00001408789,0.00002463783,0.00002821312,0.001430286,0.001767806,0.01042031,0.9578955,0.02767898],"study_design_scores_gemma":[0.0001204714,0.00001831518,0.0009368378,0.00009805834,0.00001377672,0.00005491899,0.00001067087,0.003961431,0.002078655,0.01014274,0.9825316,0.00003265899],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.002149773,0.0007480684,0.05464,0.0018171,0.008262622,0.0005604625,0.5146328,0.05014966,0.3670396],"genre_scores_gemma":[0.02343912,0.001321563,0.04749242,0.00149645,0.001342311,0.001598058,0.4459207,0.05073285,0.4266565],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.7486444,"threshold_uncertainty_score":0.3585282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03407267538052539,"score_gpt":0.258804638071857,"score_spread":0.2247319626913316,"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."}}