{"id":"W6946809501","doi":"10.34943/772ac7a3-ab5d-4e7c-b01f-e6351b6fd14d","title":"Sharp Point Accelerometer Deployed 2019-06-07","year":2021,"lang":"en","type":"dataset","venue":"Ocean Networks Canada Society","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Accelerometer; Software deployment; Acceleration; Measure (data warehouse); Point (geometry); Global Positioning System","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":[0.0006915906,0.001735662,0.0008928546,0.001520136,0.000752066,0.001076389,0.001888034,0.001097485,0.01480995],"category_scores_gemma":[0.00244554,0.0003368939,0.0004982598,0.002887134,0.0003718839,0.001002698,0.001154879,0.001306408,0.04951661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00107245,"about_ca_system_score_gemma":0.001482045,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05563586,"about_ca_topic_score_gemma":0.1183695,"domain_scores_codex":[0.9991783,0.0000894802,0.0000672319,0.0001966888,0.0003265405,0.0001418508],"domain_scores_gemma":[0.9989237,0.00006954974,0.00005054555,0.0002430378,0.0006194261,0.00009371372],"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":[0.00007570675,0.00003519818,0.001371504,0.0001303533,0.00001296424,0.00003716007,0.00002643927,0.0005428264,0.0003320954,0.0004570529,0.9925668,0.004412013],"study_design_scores_gemma":[0.0001625604,0.00004985619,0.01725812,0.0001491536,0.00001804301,0.0001148622,0.0002447291,0.002666194,0.001581768,0.001420049,0.9762832,0.00005136546],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001642901,0.00007712932,0.0004234718,0.0001660573,0.0001189724,0.00004496567,0.9922577,0.001381077,0.003887754],"genre_scores_gemma":[0.001843147,0.00003994579,0.0005732263,0.00005047574,0.00001163278,0.00005843268,0.9956832,0.00007662621,0.001663304],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9443641,"threshold_uncertainty_score":0.1106241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03157933981640267,"score_gpt":0.2750806267728687,"score_spread":0.243501286956466,"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."}}