{"id":"W4411751858","doi":"10.7818/ecos.2954ms1","title":"APPENDIX1: Alberta Avifaunal Data (long form dataset)","year":2025,"lang":"en","type":"article","venue":"Ecosistemas","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.0002291246,0.0001300972,0.0001429238,0.00002364076,0.0001883735,0.00007270108,0.0008696253,0.00005641974,0.1175015],"category_scores_gemma":[0.00006328689,0.0001187237,0.00003738127,0.0002377238,0.00009576189,0.0003425541,0.001240057,0.00008755104,0.01162214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003104993,"about_ca_system_score_gemma":0.00001011633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052321,"about_ca_topic_score_gemma":0.01581024,"domain_scores_codex":[0.9988275,0.0000251678,0.0002217643,0.0004341643,0.0002011392,0.0002902677],"domain_scores_gemma":[0.9986703,0.00005976182,0.00005841401,0.001120278,0.000003681882,0.00008759492],"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":[0.00001112619,0.0000950767,0.03477522,0.00003414044,0.00002039138,0.000006034819,0.00002563137,0.000001371746,0.000135275,0.002701814,0.9607245,0.001469466],"study_design_scores_gemma":[0.0002592255,0.00001031929,0.09681837,0.0000204592,0.00002878247,0.000005953236,0.0001753443,0.0002149025,0.0002627702,0.00008049744,0.9019811,0.0001422613],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06267853,0.0002120845,0.0003932935,0.004140954,0.0007673727,0.0004921711,0.005243692,0.00008508729,0.9259868],"genre_scores_gemma":[0.9291098,0.00009881058,0.0001192979,0.003215771,0.00006779524,0.00005234584,0.03371202,0.00002090741,0.03360331],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8923835,"threshold_uncertainty_score":0.9891474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03817178553744495,"score_gpt":0.2910031467021205,"score_spread":0.2528313611646755,"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."}}