{"id":"W7080175659","doi":"10.5281/zenodo.17067567","title":"Data used in \"Trait–Based Adjustments: Key to Improving Model Representation of the Bloom Seasonal Cycle in the Subantarctic Zone\"","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Society of Intestinal Research","funders":"","keywords":"Bloom; Key (lock); Representation (politics); Annual cycle; Seasonality","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":[0.001326742,0.00184308,0.001284325,0.001807526,0.0007142469,0.001774734,0.002758274,0.002563477,0.03690973],"category_scores_gemma":[0.005827298,0.0006917669,0.001736779,0.003617972,0.0004819972,0.001014969,0.001535267,0.002124261,0.04904476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00143628,"about_ca_system_score_gemma":0.001813593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02912149,"about_ca_topic_score_gemma":0.04466676,"domain_scores_codex":[0.9989892,0.0001739052,0.0001336772,0.0003226603,0.0002542138,0.0001263209],"domain_scores_gemma":[0.9977555,0.0005649106,0.0001956814,0.0007339575,0.0005903372,0.0001597181],"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":[0.000125045,0.00004911833,0.001635617,0.000775092,0.00007903756,0.00004213086,0.0000368562,0.00267824,0.0004793016,0.0008327456,0.9902761,0.002990761],"study_design_scores_gemma":[0.0006261002,0.00003467,0.01161494,0.0003191576,0.00007209074,0.00008817517,0.000108411,0.004753128,0.001384233,0.003395348,0.9775213,0.00008247473],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003287859,0.0000405465,0.0002196103,0.00005718987,0.00004409225,0.00001327808,0.9982266,0.0006621651,0.0004078977],"genre_scores_gemma":[0.0009383533,0.00003387339,0.0006973234,0.00003539796,0.000005430074,0.00006710501,0.9977444,0.0001216317,0.000356451],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03690973,"threshold_uncertainty_score":0.1234754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04829138371958796,"score_gpt":0.2718291984432836,"score_spread":0.2235378147236957,"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."}}