{"id":"W7029076894","doi":"","title":"Historical records of wildlife, invertebrates and plants in Alberta","year":2021,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"Criminal Law and Policy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Invertebrate; Historical record; Historical ecology; Biodiversity; Taxon","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":[0.0004067613,0.0002260349,0.0001764644,0.006220446,0.002418288,0.001234988,0.001218731,0.0004056749,0.006839906],"category_scores_gemma":[0.001048059,0.0002656605,0.0001498253,0.009447533,0.001179531,0.0003824656,0.0008433002,0.0003952582,0.001262319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00934186,"about_ca_system_score_gemma":0.00604735,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9629478,"about_ca_topic_score_gemma":0.9926234,"domain_scores_codex":[0.9994609,0.00002570703,0.00002803293,0.00009792585,0.0002424809,0.0001450547],"domain_scores_gemma":[0.9980385,0.0001368309,0.0003615846,0.00008860513,0.001040348,0.0003342759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001926726,0.00004213555,0.8631265,0.0004893344,0.0001055066,0.001103828,0.008787903,0.001173281,0.002002108,0.003192094,0.02538894,0.09439574],"study_design_scores_gemma":[0.000001931628,0.000008911908,0.9545528,0.0001083684,0.00002253452,0.0002656195,0.002910356,0.0001514547,0.0003243166,0.0001148161,0.04152532,0.00001363677],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8631175,0.008958347,0.001089756,0.0004298393,0.0000670542,0.00007525831,0.04274714,0.0002028584,0.08331227],"genre_scores_gemma":[0.9280487,0.00475707,0.002025876,0.000168974,0.00002959214,0.00003974883,0.01999873,0.00004130596,0.04489006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03705221,"threshold_uncertainty_score":0.07454079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02520178979423006,"score_gpt":0.293649288140037,"score_spread":0.2684474983458069,"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."}}