{"id":"W7036280516","doi":"","title":"Aviary Specialization Changes","year":2020,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Urbanization; Habitat; Metropolitan area; Population; Index (typography); Climate change; Population decline; Seasonality","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":[0.000505366,0.0004150033,0.0003848121,0.001350409,0.0004239266,0.0006708819,0.0004452942,0.0002212372,0.00652134],"category_scores_gemma":[0.001509185,0.0001566226,0.0005089464,0.001975333,0.0003075138,0.0004270092,0.0006752978,0.0004103683,0.001554465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009895684,"about_ca_system_score_gemma":0.0004988682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02606606,"about_ca_topic_score_gemma":0.0584684,"domain_scores_codex":[0.9994292,0.00005696747,0.00002541014,0.0002302468,0.0001236078,0.0001346719],"domain_scores_gemma":[0.9990212,0.0001416007,0.0003586859,0.000136836,0.0001635989,0.0001780302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002456247,0.00006945594,0.8855208,0.0005205364,0.0004222278,0.000446562,0.001042741,0.001197095,0.02999843,0.001058541,0.01786093,0.06161708],"study_design_scores_gemma":[0.000002070723,0.00001751714,0.9913796,0.00001242166,0.00002148102,0.00009749889,0.0001227438,0.0002979909,0.0007819716,0.0001533351,0.007104708,0.000008583655],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9148164,0.001115634,0.003905973,0.000262407,0.00004327121,0.00007224394,0.0633835,0.0006287023,0.01577196],"genre_scores_gemma":[0.9426987,0.000754545,0.003384845,0.0002268477,0.00003308271,0.0001998561,0.04484173,0.0002610418,0.007599425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02606606,"threshold_uncertainty_score":0.05182868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008813172654362935,"score_gpt":0.2675572588239801,"score_spread":0.2587440861696171,"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."}}