{"id":"W6931662855","doi":"10.5281/zenodo.7557101","title":"tati-micheletti/fitBirdBiomassModel: Release v.1.0.0","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Boreal; Biomass (ecology); Anticipation (artificial intelligence); Function (biology); Taiga","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001558514,0.003095218,0.001901046,0.001331768,0.0006311063,0.002045298,0.003514508,0.002353572,0.1922832],"category_scores_gemma":[0.003912656,0.002174995,0.003113203,0.0008135251,0.0003733319,0.001491579,0.001848998,0.002932351,0.1315747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008452704,"about_ca_system_score_gemma":0.001456004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01051568,"about_ca_topic_score_gemma":0.01230212,"domain_scores_codex":[0.9996594,0.00009028792,0.00002515767,0.00009652563,0.0000567466,0.00007193885],"domain_scores_gemma":[0.9990633,0.0005278647,0.00005673499,0.0001321032,0.000140651,0.00007935285],"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":[0.0005073088,0.0002517816,0.007356019,0.001183012,0.001013584,0.0003105954,0.0002599835,0.1164224,0.00275617,0.01390745,0.8056403,0.05039144],"study_design_scores_gemma":[0.0005707292,0.0001221236,0.00279571,0.0002836412,0.0003554963,0.0003102468,0.00007279789,0.4915734,0.00511684,0.02530486,0.4732752,0.000218998],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.00719833,0.0006679333,0.3615788,0.0005693973,0.0005726085,0.0003087053,0.1828655,0.4300918,0.01614701],"genre_scores_gemma":[0.07542169,0.0009413479,0.2199381,0.001337667,0.0003965576,0.00282006,0.2837679,0.3673198,0.04805685],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.1922832,"threshold_uncertainty_score":0.6432513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02475305817869633,"score_gpt":0.2337927739643108,"score_spread":0.2090397157856145,"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."}}