{"id":"W6931625358","doi":"10.5683/sp3/zrd2at","title":"Akimiski Island Ontario. 1:50,000. Map Sheet 043A14, ed. 1, 1994","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Raster graphics; Natural (archaeology); Aerial photography; Digital mapping; Government (linguistics); Geographic information system; Viewshed analysis","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":[0.0003203862,0.001571171,0.001257618,0.004399851,0.001083149,0.002229829,0.001506429,0.0004625646,0.1233034],"category_scores_gemma":[0.001861956,0.0007938017,0.00049858,0.02144004,0.000299515,0.0008625737,0.0007466496,0.0008538439,0.1030536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005226729,"about_ca_system_score_gemma":0.01062656,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7760659,"about_ca_topic_score_gemma":0.86804,"domain_scores_codex":[0.9996096,0.00001885616,0.00003635825,0.0001083882,0.0001365411,0.00009026371],"domain_scores_gemma":[0.9987679,0.00009295627,0.0001456564,0.0001515151,0.0006870583,0.0001550372],"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":[0.00003214978,0.000007619727,0.002043804,0.000478733,0.00001905438,0.00002237765,0.00005445649,0.0001361713,0.00007504388,0.000238638,0.991345,0.005546961],"study_design_scores_gemma":[0.00004460569,0.00000358594,0.02219461,0.0001669662,0.00001987734,0.00002910006,0.0001934189,0.0001322639,0.0001412626,0.0002010194,0.9768561,0.00001716663],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001155311,0.0000455967,0.00001818153,0.00001464455,0.000005493708,0.000003921491,0.9982914,0.00006233958,0.001442846],"genre_scores_gemma":[0.0006014679,0.0001372424,0.0001732775,0.00001111778,0.000002676477,0.00004261135,0.9944365,0.00005353419,0.004541452],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2239341,"threshold_uncertainty_score":0.4505058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008624829611479236,"score_gpt":0.2360705105946639,"score_spread":0.2274456809831846,"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."}}