{"id":"W6910951583","doi":"10.5061/dryad.f7m0cfxwj","title":"Ecological inference using data from accelerometers needs careful protocols","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Proteogenomics; Noise (video); Limiting; Work (physics); Feature (linguistics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.1612702,0.002579406,0.003316793,0.004585141,0.004127072,0.007816706,0.007889905,0.004297633,0.01102601],"category_scores_gemma":[0.3629339,0.00265159,0.003372476,0.005325033,0.007057541,0.007932709,0.007631488,0.008434425,0.00735001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001739512,"about_ca_system_score_gemma":0.005946259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004873815,"about_ca_topic_score_gemma":0.009102758,"domain_scores_codex":[0.8086036,0.1210018,0.03014539,0.00985833,0.02896869,0.001422235],"domain_scores_gemma":[0.5521914,0.1879647,0.01495988,0.1432454,0.09951919,0.002119455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002928967,0.001375705,0.04516171,0.0145444,0.002006094,0.002690741,0.0179344,0.009914145,0.05160157,0.06136656,0.1206093,0.6698664],"study_design_scores_gemma":[0.0007122282,0.001203623,0.06918386,0.01483074,0.0007781977,0.001754746,0.008665648,0.02038675,0.02870926,0.1690499,0.6835532,0.001171965],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.01715928,0.002779128,0.8971229,0.009618625,0.004995977,0.03807615,0.009503071,0.003187711,0.01755708],"genre_scores_gemma":[0.05194939,0.002097283,0.8640909,0.004788378,0.001439189,0.06520024,0.004177141,0.001192764,0.005064652],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.1612702,"threshold_uncertainty_score":0.8528888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2584012429364161,"score_gpt":0.3673444949422077,"score_spread":0.1089432520057916,"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."}}