{"id":"W6912443251","doi":"10.5281/zenodo.3620824","title":"Wading Deep into Canal Spatial Data: The \"Geo\" in RDM","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Landscape and Cultural Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"RDM; Metadata; Geospatial analysis; Visualization; Data visualization; Data management; Focus (optics); Geospatial metadata","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01603878,0.0004088884,0.0003997224,0.004381729,0.003208485,0.01055326,0.002334646,0.002165743,0.01059255],"category_scores_gemma":[0.03781254,0.0007292563,0.0006613504,0.009102806,0.008956229,0.01816834,0.01176742,0.004967446,0.004088194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004510024,"about_ca_system_score_gemma":0.008629558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03749468,"about_ca_topic_score_gemma":0.06358336,"domain_scores_codex":[0.9922385,0.003617364,0.0006441079,0.0006536297,0.002459009,0.0003874813],"domain_scores_gemma":[0.9802612,0.008927839,0.0007117615,0.005747054,0.003389243,0.0009628255],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006151965,0.00003044084,0.003135795,0.0004100592,0.000017244,0.0004604975,0.01981547,0.000698598,0.002629451,0.5624436,0.1720789,0.2382186],"study_design_scores_gemma":[0.00000506457,0.000009139425,0.000508576,0.0002891002,0.000004357031,0.0001786348,0.002602087,0.0004508048,0.0009800736,0.02530896,0.9696344,0.00002889854],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01584859,0.007135233,0.6829229,0.1329212,0.008226148,0.0004922848,0.008342111,0.0112186,0.132893],"genre_scores_gemma":[0.1202931,0.007118574,0.7819907,0.02201034,0.001891019,0.0007594036,0.007093842,0.008100162,0.05074291],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9839612,"threshold_uncertainty_score":0.08482224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07443522501909143,"score_gpt":0.2379165098242363,"score_spread":0.1634812848051449,"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."}}