{"id":"W1557876356","doi":"10.1161/str.46.suppl_1.tmp102","title":"Abstract T MP102: Hotline Use for Recruitment Support in Acute Stroke Trials: Lessons learned To Date in Antihypertensive Treatment of Acute Cerebral Hemorrhage (ATACH)-II","year":2015,"lang":"en","type":"article","venue":"Stroke","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Abbott (Canada)","funders":"","keywords":"Hotline; Medicine; Clinical trial; Context (archaeology); Stroke (engine); Acute stroke; Randomization; Medical emergency; Emergency medicine; Randomized controlled trial; Emergency department; Internal medicine; Nursing; Telecommunications","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":[0.05122932,0.0005390992,0.001158673,0.0009876536,0.0008049253,0.004092355,0.001760401,0.002196794,0.02932101],"category_scores_gemma":[0.1347466,0.000383725,0.0008343486,0.001980477,0.0006583423,0.002843479,0.001837954,0.002314728,0.008421929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001269114,"about_ca_system_score_gemma":0.006366185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001910516,"about_ca_topic_score_gemma":0.00382771,"domain_scores_codex":[0.9690148,0.02437861,0.002534036,0.000673844,0.002728975,0.000669788],"domain_scores_gemma":[0.8513328,0.1000618,0.01501074,0.006913172,0.01635498,0.01032647],"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":[0.006648231,0.0006306047,0.01085111,0.004295006,0.0002504412,0.0001371097,0.0009043253,0.0003794869,0.0007575012,0.0007118671,0.1560004,0.8184338],"study_design_scores_gemma":[0.01986276,0.02740827,0.4793934,0.02311974,0.002080217,0.001055912,0.005175367,0.009906732,0.006042339,0.00763729,0.4176566,0.0006613688],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.3044406,0.07321966,0.04078524,0.3841035,0.009337034,0.01986742,0.02765861,0.0105447,0.1300432],"genre_scores_gemma":[0.6635993,0.04695196,0.1198669,0.05326674,0.02094763,0.02497984,0.02024196,0.002568561,0.04757708],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05122932,"threshold_uncertainty_score":0.2709298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6426187705800542,"score_gpt":0.5325084714410053,"score_spread":0.1101102991390489,"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."}}