{"id":"W2743116518","doi":"10.3897/tdwgproceedings.1.20155","title":"Spatial Visualization of Publicly Accessible Species Occurrence Data","year":2017,"lang":"en","type":"article","venue":"Biodiversity Information Science and Standards","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Treasury Board of Canada Secretariat","funders":"","keywords":"Geospatial analysis; Metadata; World Wide Web; Resource (disambiguation); Geographic information system; Database; Environmental resource management; Geography; Computer science; Remote sensing; Environmental science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001742499,0.0007087765,0.0005289483,0.01008251,0.0007005411,0.002648318,0.0008260998,0.0005239819,0.02071927],"category_scores_gemma":[0.006815154,0.000307903,0.0006723349,0.01257618,0.0002997875,0.001455893,0.002665827,0.000865533,0.004972924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008979535,"about_ca_system_score_gemma":0.002112878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02854245,"about_ca_topic_score_gemma":0.03324361,"domain_scores_codex":[0.9987759,0.0001807875,0.0001190288,0.0002401692,0.0005388389,0.0001452212],"domain_scores_gemma":[0.994995,0.002301983,0.0004917966,0.0007430302,0.001167733,0.0003004472],"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":[0.001447752,0.0005077154,0.05149768,0.002932286,0.0003820423,0.001243524,0.009730786,0.01751216,0.01426377,0.02145272,0.6169441,0.2620853],"study_design_scores_gemma":[0.0002300536,0.0001388535,0.1261885,0.001207705,0.0001884417,0.0004815286,0.006065573,0.06853715,0.01698374,0.01799264,0.7616987,0.0002870999],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.109407,0.001065483,0.04418886,0.002870481,0.0007313518,0.0003601761,0.6967734,0.0842559,0.0603473],"genre_scores_gemma":[0.4325239,0.00165989,0.1340217,0.0003001967,0.0003133318,0.001086522,0.4100498,0.00746372,0.01258088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02854245,"threshold_uncertainty_score":0.06931281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09412242396131154,"score_gpt":0.3697400619283489,"score_spread":0.2756176379670373,"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."}}