{"id":"W4407569937","doi":"10.29173/bluejay6408","title":"Nature Saskatchewan Member Spotlight: Spencer Sealy","year":2025,"lang":"en","type":"article","venue":"Blue Jay","topic":"Polar Research and Ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Library science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002220402,0.00008576502,0.0001008124,0.00003504459,0.0001135148,0.00002530428,0.0002913469,0.0001563878,0.01161661],"category_scores_gemma":[0.00006057175,0.00007001206,0.00004754816,0.0002568862,0.0001273603,0.0001079992,0.0002638828,0.0003461204,0.004020214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001388177,"about_ca_system_score_gemma":0.00004226098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004778905,"about_ca_topic_score_gemma":0.005441911,"domain_scores_codex":[0.9990429,0.00004834596,0.00009583563,0.0002477614,0.0001864245,0.0003787914],"domain_scores_gemma":[0.9995798,0.00004226242,0.00001864912,0.0002448508,0.000004411244,0.0001100235],"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":[0.00008675469,0.0002252475,0.3284138,0.00002737497,0.00006158947,0.0001307348,0.001125256,0.0001676935,0.02388857,0.001101137,0.6248273,0.01994448],"study_design_scores_gemma":[0.0002426959,0.0000286698,0.2763099,0.000007064632,0.000006625685,0.000004995171,0.0002141232,0.0001297398,0.01080702,0.001497489,0.7106355,0.0001161854],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8175071,0.000104469,0.00004889388,0.003080154,0.0002424813,0.0001450771,0.000005547989,0.0000400063,0.1788262],"genre_scores_gemma":[0.9349363,0.00001283596,0.0003162483,0.001687031,0.00004398737,0.00001173051,0.000003908703,0.000006510374,0.06298143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1174291,"threshold_uncertainty_score":0.9967552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006041208932032239,"score_gpt":0.2718934651316513,"score_spread":0.2658522561996191,"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."}}