{"id":"W4402262283","doi":"10.62973/09-033","title":"OWS-6 SensorML Profile for Discovery Engineering Report","year":2009,"lang":"en","type":"report","venue":"","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada; Joint Program Executive Office for Chemical, Biological, Radiological and Nuclear Defense; National Geospatial-Intelligence Agency","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.009681529,0.001621601,0.001110299,0.004597952,0.001123537,0.005806101,0.002754972,0.002370388,0.05066064],"category_scores_gemma":[0.01448368,0.001492999,0.0009627563,0.002811019,0.000659328,0.004849522,0.002806466,0.002724292,0.09132401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00215811,"about_ca_system_score_gemma":0.005581346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008942197,"about_ca_topic_score_gemma":0.006323619,"domain_scores_codex":[0.9935964,0.00122131,0.0009508674,0.0003896673,0.003416103,0.0004255612],"domain_scores_gemma":[0.9904029,0.001882813,0.0006011672,0.002433561,0.004117045,0.0005624075],"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":[0.0005394828,0.0003239477,0.001107023,0.001007733,0.00003267861,0.0004778427,0.0006960027,0.004320435,0.01184555,0.0589702,0.7669781,0.1537011],"study_design_scores_gemma":[0.00004200934,0.00004250762,0.0003481105,0.0001805198,0.000009761611,0.0002008106,0.00007630101,0.003478611,0.006758802,0.004774067,0.9840432,0.00004527441],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.004400737,0.000802346,0.5381848,0.003175353,0.001015714,0.003473214,0.1499279,0.1439178,0.1551023],"genre_scores_gemma":[0.01866948,0.001603841,0.3139453,0.001350898,0.0003724124,0.004198879,0.4565446,0.04269534,0.1606192],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05066064,"threshold_uncertainty_score":0.1694767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.029342068734002,"score_gpt":0.3278626342299492,"score_spread":0.2985205654959472,"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."}}