{"id":"W4394327240","doi":"10.6084/m9.figshare.1228793","title":"Squirrel Abundance as a function of habitat and other factors","year":2014,"lang":"en","type":"dataset","venue":"Figshare","topic":"Animal Ecology and Behavior Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Abundance (ecology); Habitat; Function (biology); Geography; Ecology; Biology; Evolutionary biology","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":[0.0003071006,0.0001941457,0.0003824457,0.0005769168,0.0003382845,0.0003687798,0.0001654739,0.0001455858,0.002467954],"category_scores_gemma":[0.0007195735,0.0001627525,0.0002166095,0.0004833243,0.0003161411,0.0002109725,0.0002685113,0.0002979386,0.0002761418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000990047,"about_ca_system_score_gemma":0.0003211805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08968662,"about_ca_topic_score_gemma":0.2905119,"domain_scores_codex":[0.9997839,0.00004318106,0.00001295304,0.0000710801,0.00004212919,0.00004675964],"domain_scores_gemma":[0.9988682,0.0002695473,0.0002510816,0.00008938183,0.0002021584,0.0003195884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009577803,0.00008439871,0.9709845,0.00003850856,0.00008672651,0.0001001957,0.000275101,0.0003049794,0.02382993,0.00002752912,0.0005697053,0.002740603],"study_design_scores_gemma":[0.000002439349,0.00005880524,0.9994462,8.250334e-7,0.000005289217,0.00001780269,0.000071669,0.00008108478,0.0002146361,0.000002564469,0.00009716042,0.000001576438],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9985862,0.00006383451,0.00005854567,0.00001642688,0.000003056532,0.00000725796,0.0008586544,0.000006429706,0.0003995633],"genre_scores_gemma":[0.997345,0.00005325705,0.0001654321,0.00001812375,0.000003327093,0.00002293086,0.001377101,0.000003016463,0.001011798],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.08968662,"threshold_uncertainty_score":0.1783292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02957960577108032,"score_gpt":0.2620745425227379,"score_spread":0.2324949367516576,"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."}}