{"id":"W4385820722","doi":"10.2196/44332","title":"An Actionable Expert-System Algorithm to Support Nurse-Led Cancer Survivorship Care: Algorithm Development Study","year":2023,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Cancer survivorship and care","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of Calgary; Princess Margaret Cancer Centre; Trillium Health Centre; Niagara Health System; Queen Elizabeth II Health Sciences Centre; McMaster University; University of Waterloo; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Algorithm; Survivorship curve; Psychosocial; Autonomy; Nursing; Reimbursement; Health care; Medicine; MEDLINE; Family medicine; Cancer; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.01430654,0.001046677,0.0008213929,0.001117889,0.0008101518,0.001819888,0.00183807,0.001260717,0.002608747],"category_scores_gemma":[0.05663683,0.000443002,0.000777189,0.0007111513,0.0004410191,0.001226991,0.001270105,0.001248648,0.0003849425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001853379,"about_ca_system_score_gemma":0.005548633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01037282,"about_ca_topic_score_gemma":0.009423876,"domain_scores_codex":[0.9935225,0.003872562,0.0006603954,0.00085702,0.0008777513,0.000209779],"domain_scores_gemma":[0.9532769,0.03581661,0.001280266,0.001408205,0.007774232,0.0004438227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001326544,0.001746396,0.04329364,0.0008671891,0.0005529409,0.0004750941,0.001070114,0.5216683,0.00274293,0.006552568,0.005565875,0.4141385],"study_design_scores_gemma":[0.0002020518,0.0002102514,0.001273442,0.00007200326,0.00009545343,0.00008606525,0.0001255368,0.9929395,0.001727995,0.001681858,0.00157087,0.00001502296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1789062,0.0002744335,0.8089023,0.000621708,0.00008578507,0.004194769,0.0007927064,0.002162855,0.004059183],"genre_scores_gemma":[0.3046259,0.00009236358,0.69165,0.0001663882,0.00001660523,0.001671654,0.001108815,0.00006980824,0.0005985454],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01430654,"threshold_uncertainty_score":0.07566112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02941776560691015,"score_gpt":0.3641041368389872,"score_spread":0.334686371232077,"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."}}