{"id":"W6888560324","doi":"10.21233/ex6e-s069","title":"Government of Canada Pit [EgPm-VP] vertebrate fauna dataset","year":2018,"lang":"en","type":"dataset","venue":"Neotoma Paleoecological Database","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Paleoecology; Fauna; Vertebrate; Government (linguistics); JSON","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":[0.0006472055,0.001526452,0.001195046,0.005330352,0.002070993,0.00229386,0.002801213,0.0009284313,0.03549214],"category_scores_gemma":[0.00503159,0.0006499726,0.0007731314,0.01444269,0.0005745937,0.001006422,0.001550639,0.001561048,0.03805408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01243708,"about_ca_system_score_gemma":0.02446715,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9296408,"about_ca_topic_score_gemma":0.9636479,"domain_scores_codex":[0.9988697,0.00005176258,0.00006576322,0.0001975941,0.0005561097,0.0002590833],"domain_scores_gemma":[0.9953462,0.0002177735,0.0001963253,0.0004768002,0.003275987,0.0004868306],"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":[0.00002671316,0.000006505675,0.0008558342,0.0001373644,0.00001525033,0.00001121973,0.00002110174,0.0001151245,0.00004997791,0.0002982517,0.9970254,0.001437107],"study_design_scores_gemma":[0.0000738528,0.000005095979,0.01688917,0.0002076219,0.00002764055,0.00003079098,0.0001446406,0.0004440242,0.0003060369,0.0004984513,0.9813363,0.00003633857],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001266158,0.00002794296,0.00002929338,0.00003106297,0.000008171729,0.000006820954,0.9988005,0.0001407263,0.000828829],"genre_scores_gemma":[0.0004293519,0.00004483305,0.0001577631,0.000017895,0.000002615714,0.00002326556,0.998518,0.00004278482,0.0007634314],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07035923,"threshold_uncertainty_score":0.1415471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008006067275777419,"score_gpt":0.1967994027410867,"score_spread":0.1887933354653093,"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."}}