{"id":"W6931827015","doi":"10.5683/sp3/ncioo5","title":"Atikokan Ontario. 1:50,000. Map Sheet 052B13, ed. 1, 1970","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; General partnership; Raster graphics; Natural (archaeology); Digital mapping; Geographic information system; Aerial photography; Government (linguistics)","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":[0.0004111736,0.001806829,0.001308925,0.004427098,0.001461225,0.002865244,0.001597232,0.0005664874,0.1300937],"category_scores_gemma":[0.00266937,0.0008332045,0.0006448175,0.01758597,0.0005297086,0.001124129,0.001030851,0.0009470508,0.1434473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007336889,"about_ca_system_score_gemma":0.01448128,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8413134,"about_ca_topic_score_gemma":0.9282289,"domain_scores_codex":[0.999441,0.00002725963,0.00004087432,0.0001518069,0.00020965,0.0001293673],"domain_scores_gemma":[0.9984288,0.000116741,0.0001345992,0.0002151193,0.0009143551,0.0001904612],"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":[0.00001984761,0.000003492506,0.0007285364,0.0002846741,0.00000954582,0.00001226882,0.000038999,0.00006678081,0.00005192659,0.0002201879,0.9952345,0.003329149],"study_design_scores_gemma":[0.00002987756,0.000002783858,0.008976652,0.0001305342,0.00001019692,0.00002400606,0.0001123188,0.00006947052,0.00008611925,0.0002379709,0.9903073,0.00001278471],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008472177,0.0000770386,0.00002946666,0.00002376757,0.00001027476,0.000004952106,0.9975272,0.0001115106,0.002131064],"genre_scores_gemma":[0.0005892628,0.0001792907,0.0001964781,0.00001889177,0.000005477888,0.00003886993,0.9934727,0.00009949933,0.005399508],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1586866,"threshold_uncertainty_score":0.4352069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0289212426937654,"score_gpt":0.2583415523966645,"score_spread":0.2294203097028991,"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."}}