{"id":"W7000483507","doi":"","title":"The Evolution of Geospatial Data Discovery at MIT","year":2024,"lang":"en","type":"other","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Service (business); Data discovery; Knowledge extraction; Web Coverage Service; Big data","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":[0.01793902,0.0003799063,0.0007226907,0.006432541,0.003380039,0.01005787,0.001763381,0.001797974,0.01096981],"category_scores_gemma":[0.06364671,0.0009521088,0.000546737,0.008326599,0.004415302,0.01931745,0.006707392,0.00303008,0.002563592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007286028,"about_ca_system_score_gemma":0.00395144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02262359,"about_ca_topic_score_gemma":0.02242508,"domain_scores_codex":[0.9915431,0.003303797,0.0003505081,0.001650861,0.002870986,0.0002807808],"domain_scores_gemma":[0.9383082,0.03671386,0.00143942,0.01259791,0.008521909,0.002418655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009867682,0.00007743903,0.009441399,0.0002095239,0.0000811127,0.0002109751,0.004831268,0.003248255,0.00152409,0.5534625,0.0624714,0.3643432],"study_design_scores_gemma":[0.00002224847,0.00004416322,0.006697076,0.0004537575,0.00005132232,0.0004323485,0.002626008,0.02692755,0.003556758,0.2097697,0.7493514,0.00006762785],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1120345,0.02810977,0.3304342,0.2301223,0.002740435,0.0002502759,0.004105662,0.008439517,0.2837634],"genre_scores_gemma":[0.6399548,0.01241736,0.2764199,0.004194173,0.001769858,0.0002672894,0.003387994,0.002562162,0.05902636],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02262359,"threshold_uncertainty_score":0.0948717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02023260871544471,"score_gpt":0.2851778797486108,"score_spread":0.2649452710331661,"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."}}