{"id":"W7071366000","doi":"","title":"SHADES OF GREY: THE LEGAL TREATMENT OF GREY MARKETS IN INDIA AND CANADA","year":2010,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grey literature; Grey market; Monopoly; Government (linguistics); Trademark; Point (geometry)","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":[0.002059366,0.0001673577,0.0003344695,0.0022773,0.02053107,0.009225599,0.001906318,0.002314304,0.007809331],"category_scores_gemma":[0.01093691,0.0002932414,0.0004102057,0.004620261,0.01428326,0.001960471,0.004211052,0.004793192,0.0001863642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09275984,"about_ca_system_score_gemma":0.1189762,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9728692,"about_ca_topic_score_gemma":0.9861723,"domain_scores_codex":[0.994125,0.0006883636,0.0001327608,0.0003391084,0.00220177,0.002512957],"domain_scores_gemma":[0.992757,0.00278066,0.0007071951,0.0003210519,0.002117496,0.001316569],"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":[0.00004224046,0.00002524346,0.008578341,0.00007374171,0.00002185204,0.001132227,0.03032348,0.0004437067,0.0003037869,0.9237507,0.01600955,0.01929512],"study_design_scores_gemma":[0.00005084508,0.00006832153,0.1114418,0.001123294,0.0001957294,0.001450141,0.1744268,0.00348622,0.00174141,0.1569806,0.5486394,0.0003955035],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.3681028,0.005710807,0.00171653,0.06403349,0.0003019399,0.00008287526,0.0003965963,0.00005529471,0.5595997],"genre_scores_gemma":[0.9771259,0.001633535,0.0005010212,0.004006656,0.00003151664,0.00001532484,0.00004884298,0.00001964025,0.01661755],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.09275984,"threshold_uncertainty_score":0.6730229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03881415877704509,"score_gpt":0.280308460427665,"score_spread":0.2414943016506199,"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."}}